The carbon footprint of Media – Part 1: Digital and TV

BBC reports a 1.6 billion tons of greenhouse gas emitted globally in the process of running and serving our digital infrastructure. If we divide it among all internet users worldwide, it means 414 kg of carbon dioxide per user annually => that is the equivalent of driving 3.385 km with a recent car model, which is about one-third of what an average European driver covers in a year

So yes, this is a LOT and the industry can do more to reduce this impact. Before we present the options, let’s first set the scene.

Content 

  • What do the terms mean? 
  • Which type of media has the largest carbon footprint?
  • How to compare with others?
  • What can advertisers do to mitigate their carbon footprint?
  • What can you do as a consumer of these media to reduce your carbon footprint? 

What do the terms “greenhouse gas”, “climate change”, “carbon footprint” and “carbon neutral” mean? 

Greenhouse gases (GHGs) are gases that increase the Earth’s temperature due to their absorption of infrared radiation. Although some emissions are natural, the rate at which they are being produced has increased because of human activities (industry, construction, mining, transportation, etc.).The most common GHGs are carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), and many fluorinated gases.

Climate change: The increase of the Earth’s temperature is the main consequence of changes in our climate that not only raise the external temperature but generate extreme precipitation and acidification as well as warming of oceans, which changes the cycle of water. Climate change has been occurring since the start of the Industrial Revolution in the 1820s. 

Due to humans’ heavy reliance on fossil fuels, energy usage, and constant deforestation, the amount of greenhouse gas in the atmosphere is increasing, which makes greenhouse gas footprint harder to reduce. However, there are several ways to achieve this, for example by choosing more energy-efficient eating habits or household appliances, increasing the usage of fuel-efficient cars, and saving electricity.

Carbon footprint, or GHG footprint: A greenhouse gas footprint is the numerical quantity of the GHGs that a single entity or action emits. It can be calculated at any level of granularity (from individual action or product to the entire planet). The latest climate science findings were published in the IPCC Sixth Assessment Report which explains that the only way to avoid a temperature rise of 1.5 °C or 2 °C is to massively and immediately cut down greenhouse gas emissions.

Carbon neutral: Carbon neutrality means the absence of GHG emissions in the atmosphere. It is generally achieved by avoiding or offsetting carbon emissions. 

Which type of media has the largest impact in terms of carbon footprint?

We will start this first part with TV, Video, Display, Print, and Social Media. A second article will follow with Out Of Home, Audio, and Emails.

Carbon footprint estimates are sensitive to many factors: 

  • Type of content: images, music, or videos. Every type of content watched has a different impact as it could be a fully fledged indoor setting with a lot of lighting involved or a reality TV adventure recorded from two small hand cameras or a selfie wheel on TikTok
  • Type of network: terrestrial, satellite, or mobile
  • The energy mix of the country where the content is consumed as energy is one of the main drivers of the GHGs emissions in Advertising. 

It is important to note that each study has its own method of calculation, and we can only recommend reading the analysis’ methodology behind the provided figures to get the full picture. Now let us take a look at the illustrations of the impact that our industry produces. 

Carbon footprint of watching TV 

For instance, the 2011 IEEE International Symposium on Sustainable Systems and Technology study estimates the carbon footprint of one hour of broadcast TV (terrestrial) at 88 gCO2eq per watcher. The carbon footprint includes both content production (12-35%) and distribution (10-28%) as well as the energy consumed by the TV set => it does not include the production of the TV device itself.  
A study conducted in 2021 gives the following estimates. It illustrates the great difference between individual European countries, essentially around the energy mix (the high proportion of fossil fuel energy is impacting the emissions drastically). The second factor is the use of internet protocols to serve video content, which requires an energy-hungry infrastructure. These estimates do not take into account the carbon footprint of device production. 

From the LoCaTe Project final report
  • Digital Terrestrial Television (DTT)
  • Over-the-top (OTT)
  • Managed Internet Protocol Television (IPTV)

Carbon footprint of watching streaming services

Streaming services such as Netflix, Youtube, Hulu, Prime, or TV+ are served through digital platforms. The Carbon Trust reports an average of around 56gCO2eq per hour of watching.

The Carbon Trust whitepaper includes a good illustration of the steps necessary to serve these services. The team based their estimate on these steps and differentiated taking into account the device connected: mobile, desktop, or TV.

From the Carbon Trust

The footprint (related specifically to the energy consumption by the viewing device) of watching content on a 50-inch TV is roughly 4.5 times that of watching on a laptop, and roughly 90 times that of watching on a smartphone. The researchers present the results broken down not only by the type of device but also depending on the quality of the image. The chart below shows how this quality factor actually impacts the GHGs emissions of the devices for different streaming services. 

From the Carbon Trust report

The figures for the conventional one indicate clearly that watching streaming services has more impact with smart TVs due to their higher energy consumption (TV sets manufacturing is not taken into account here). 

Carbon footprint of Social Media usage on mobile devices

Greenspector published a study in 2021 estimating the gCO2eq per one minute of usage on a Standard Smartphone (Samsung S7) with the staggering figures for TikTok: the estimated emissions reach  2.5gCO2eq per minute of usage versus only 0.46gCO2eq for YouTube (based on the energy mix in France and locations according to the methodology described here).

This translates into 180gCO2eq per hour on TikTok versus 27.6gCO2eq on Youtube. 

One factor with a great impact on the outcome of the calculation is the amount of data exchange generated by the consumption of content on mobile devices. As we have seen before, the data flow impacts the overall volume of GHGs emitted. 

With an average usage time of over 2 hours daily, Greenspector presents a total estimate of 60kgCO2eq per year per person. So teenagers spending Sundays binge watching (ok, 8 hours is binging for me) TikTok equates to 10km on an airplane. 

This study led to the creation of a social media usage calculator that one can check out here.

Carbon footprint of display campaigns

The estimated carbon footprint of a digital campaign, as demonstrated above, depends on the elements we wish to take into account: 

  • Production of the ad (from photo shooting to design)
  • Transmission of it (data centers and servers) based on creative weight
  • The platform where it is delivered (social media, publishers’ site on the open web)
  • Reception (based on the device to view the ad).

One can also argue that it could include: 

  • Website traffic generated by the campaign 
  • Product sales uplift generated by the campaign (in this case, including the carbon footprint of the product or service itself). 

Once again, carbon footprint estimation is a really complex topic so the best we can do is scratch the surface and provide a general idea of carbon footprint. There are multiple approaches and methodologies, and each one of them is unique. For instance, Mediacom and CO2Balance developed a carbon calculator for the UK market, covering OOH and digital but omitting data transmission. 

In parallel, the Good Loop is offering another model which relies on the energy mix as well as the size (e.g. in MB) and volume of impressions to provide an estimate of digital campaigns’ carbon footprint (considerations and limitations are not indicated). 

The calculator estimates that a 15,000,000 impressions campaign using a typical display format (let’s say a medium rectangle – 40 KB) equals 324kgCO2eq of emissions. When this campaign serves 1,500,000  30” video ads weighing 200 MB on Youtube, the carbon footprint reaches 162,000 kgCO2eq, or 162 tons of CO2 equivalent.

How many campaigns have you booked this year? 

How to compare with others?

According to The Nature Conservancy, the average carbon footprint for a person in the United States is 16 tCO2eq, one of the highest rates in the world. Globally, the average carbon footprint is closer to 4 tons.

Eurostat reported an average of 6.8tCO2eq per European in 2019.  

If you wish to compare yourself to any other benchmarks, do not hesitate to take a look at the Co2 of everything page. 

According to Ericsson, the total carbon emissions produced by the Information and Communications Technology (ICT) industry are equivalent to the volume of fuel consumed by the Airlines industry over a year. But the needs of the digital industry and its consumption volumes are growing at a much higher pace. 

What can advertisers do to mitigate their carbon footprint?

Although we are living in an increasingly digital world, the ICT sector remains at around 1.4% of the global carbon emissions. Its footprint could be reduced by a staggering 80% if the electricity it consumes came from renewable energy sources instead of fossil fuels.

Generally, there are a few steps that can have a huge positive impact on the environment.

  1. Define low-carbon production guidelines: 

For instance, avoid shooting overseas when the team would have to travel by plane:

  • => hire a local team and work with them remotely 
  • => shoot in your country of origin
  • => international brands can localise shooting. 
  1. Reduce the weight of creatives:  The Shift Project has developed guidelines on how to reduce the weight of any videos. It applies to advertising as well: 
    • Limit the digital format weight – reduce the weight by avoiding HD ads or using technology to make your HD videos lighter. 
    • Shorter videos: cutting a 30’’ video down to 15’’ is already dividing your footprint by two.
  2. Compensate carbon emissions beyond the business ones:

As mentioned above, it is possible to compensate for any carbon impact that was already measured, or to decide to attribute a lump sum to offset further impact of the products or services; for instance by dedicating budgets to support innovation in carbon retention or cover beyond the carbon footprint of your own products or services. 

  1. Encourage your partners to use green energy:

As advertisers and agencies, you have the power to demand transparency over the energy use and ask providers about their progress in terms of emissions reduction. Every participant of this sector can start moving in the right direction, as The Trade Desk claims in the article they published a few days ago. Stewardship is a very efficient way to mitigate the overall impact of the industry, and it is essential that every actor practise a conscious approach. 

What can you do as a consumer of these media to reduce your carbon footprint? 

  1. Watch less video on the go – better view the videos when you are connected to WiFi.
  2. Change your mobile phone settings to a lower video resolution (SD versus 4k).
  3. Cancel autoplay of videos and close browser windows running videos in case they stay in the background. 
  4. Turn off your devices at the end of the day.
  5. Give yourself some “flight mode” breaks, 
  6. Why not erase your social apps from your phone

Cookie Life – Part 5: Universal Identifiers

I wrote this article as part of a series published on the Mercury Media Technology GmbH blog.

As presented before, the technology behind cookies has made digital advertising extremely efficient. By offering precise information on consumer preferences and behaviours, advertisers could select the personas and demographics which best fit their product to maximize the ROI. 

Publishers needed to provide the right environment to motivate these audiences to dwell on their platforms, within or outside the walled gardens.

As explained in Part 3 of the series, it is possible to find alternatives avoiding the use of cookies. However, this would mean that agencies and clients have to agree to consider these alternatives as potential opportunities to grow differently, then test them for validation purposes. 

Why need cookie alternatives like universal identifiers?

As mentioned in our article about the current cookie status quo => Simple. Money. 

When cookies are gone, it will be impossible to directly identify website visitors based on their browser history.Therefore, it will be unfeasible to serve them personalised ads adapted to their profile. 

For advertisers, this will limit the capacity to attribute, target and monitor campaigns. 

=> Not wasting money and making more money. 

It is a question of targeting for advertisers – not wasting advertising money on audiences who would never consider or buy their products or services. When an advertiser chooses to bid “blindly”, it will buy cheap impressions but its cat food ads can be served to dog lovers, which would be pure waste. One can say that some products – like washing powder or shampoo – can actually be served universally, but Italian luxury brand Salvatore Ferragamo used the Times’ first-party demographics and interests data for segmentation to drive a 0.47% CTR in its campaign (Source: WARC) – i.e. 9.4 times higher than the IAB benchmarks costs.

For publishers, it is a question of revenue. An identified bid request is paid way more than an unidentified one. Offering no visitor segmentation whatsoever diminishes the quality of ads served in the specific ad slot too and requires diversifying sources of income – the ad slots – to maintain the revenue, which decreases the general content quality of the website. 

An individual publisher, however big it is, cannot create the same audience group or interest pool as the walled gardens with its visitors alone, therefore potential collaboration with others is beneficial. That is the reason why the universal identifiers came around – the status quo that the industry needed to find new ways to scale. 

“We don’t want one ID, but we also don’t want 20 plus either”. Mathieu Roche, CEO and founder of ID5

How do universal identifiers work?

The goal is to be able to keep following users across the web. Why? Because it enables the control over the number of exposures and successful touchpoints of each advertising campaigns. 

Users are now connecting digitally through devices beyond mobile and desktop, fragmenting the market further. They are now exposed to ads in various channels and marketers aim to maximise the efficiency of their activities at the cross-channel and cross-device level. 

Moreover, the pressure to respect privacy of each user is growing and being enforced more rigorously.

Two types of identifiers have emerged on the market:

– Deterministic

These identifiers are a combination of the first-party website ID and hashed and encrypted PII such as an email address or telephone number. This kind of ID will remain open and ubiquitous while introducing significant upgrades to consumer privacy (compliant with privacy laws) and transparency. 

The problem for now is that this technology needs to be scaled in order to be properly applied: the capacity to match the IDs across platforms depends on the adoption rate (the number of participating publishers) – the larger the group of publishers using them, the more relevant and ubiquitous their data will be. 

– Probabilistic

Providers are using machine learning algorithms to extend the ID with signals such as clicking, visiting a page, or buying products. It is mirroring the ID partners from its sources to other ID-sourced partners to offer broader identification opportunities. 

The idea itself is great and could compensate the scalability problem that the deterministic IDs have. 

Some of the competitors on the market

MMT - Example of universal identifiers available

Ok, now. What should marketers do about universal identifiers?

The problem is, we do not know yet what the future holds and which ID solution(s) will prevail. The market is going through a transformation and the landscape is still shaping itself but marketers should not sit around and wait until they see the results. 

As explained in this series, strategies and solutions are already available to go beyond the third-party cookies, and identifiers are one of the possible solutions under development that marketers need to keep track of. 

Brands have a role to play in building tomorrow’s market by joining the conversation and ensuring that the different technologies can work with one another. 

Any provider has to be transparent about its privacy compliance, hence the technology behind the identification. Marketers should get familiar with the technologies and solutions in order to avoid surprises, understand limitations and be comfortable with market changes. 

As for the walled gardens, advertisers should not build a dependence on a single source of audience insights for campaign efficiency assessment. 

MMT Consulting can help marketing teams assess their dependence on third-party solutions and provide recommendations on how to create the most relevant future-proof data-driven solutions to run your marketing campaigns. MMT is independent from any providers, keeping an agnostic point of view adapted to advertisers’ and agencies’ needs. Get in touch! 

Sources

Cookie Life – Part 4: Data Clean Rooms

I wrote this article as part of a series published on the Mercury Media Technology GmbH blog.

As part of our series discussing the evolution of digital advertising triggered by the concerns about privacy on the web, we have published articles on how to target consumers without third-party cookiesand how to start collecting first-party data. This piece aims to clarify how you can benefit from data clean rooms when you use your first-party data for advertising purposes. 

Content:

  • What are “data clean rooms” in the context of advertising? 
  • How do data clean rooms work?
  • Why set up a data clean room for your company?
  • How to get started with a data clean room?
  • What are distributed clean rooms?
  • What are deficiencies of data clean rooms?

What are “data clean rooms” in the context of advertising?

The name “clean room” originates from manufacturing sites that require extreme protective measures to prevent contamination. 

Definition Data Clean Rooms

data clean room in advertising is a safe space that offers access to sets of aggregated & anonymized PII data that can be cross-matched for measurement, analytics, and targeting purposes.

Foggy? Let start with some explanations: 

  • Safe space: privacy-first closed-environment with pre-defined requirements to keep the data anonymized.
  • Aggregated & Anonymized: individual first-party user information is #ed (read hashed for unrecognizable characters) and grouped by clusters. No cluster can be limited to an individual or a few profiles. 
  • Matching: level of relevance of the two distinct audiences, one versus the other. 
  • PII data: (Personally Identifiable Information) any information that can identify a user: email, phone number, name, etc.

How do data clean rooms work?

Let’s take an example! The most famous use case is the walled gardens: they have individual data from billions of users, but they only provide access to anonymized data in cohorts to the marketers willing to leverage it. Advertisers of all sizes can define target groups by selecting a set of variables, from location to interests. The profiles of users are anonymized, and the advertisers can see the delivery data but no individual identities (PII). A clean room is a “neutral“ storage in the sense that no personal data can be extracted by any stakeholders: in the case of walled gardens, the advertisers can leverage it without seeing the names and profiles of users, which solves the issue of user privacy. 

If the advertiser has its own first-party data collection solution, it has the capacity to create its own cohorts. By building a proprietary solution or using partners available on the market, it can aggregate and anonymize its own data to match with other partners. No individual profile will ever be shared.

Data Clean Rooms_mmt_Cookie Life 4

Why set up a data clean room for your company?

  • Accessing data from partners without giving away your first-party data: Brands can protect the PII information they have been entrusted with by their customers and fans. Still, they can use it to find their alter-egos on the web (open or walled gardens) without any risks of breaching privacy laws. 
  • Scaling your first-party audience from the start: When you decide to ramp up your first-party data collection effort, optimising the strategy and acquiring a loyal customer base takes time. Clean rooms allow brands to multiply their audience very quickly. 
  • Assessing external partners based on the audience matching rate: Building the right partner synergies requires thorough scrutiny of both sides – the most efficient partners and audiences. 

How to get started with a data clean room?

Data clean rooms provide the right technical environment to apply your first-party data before interacting with other data sets. There are precise requirements to fulfill in order to connect CRM solutions to it. They need good quality data and good data governance to be used to the fullest, which may entail hiring data scientists and an analytics team to manage clean rooms. 

To get you started in your setup, please consider the following: 

  • If you have already set your own tech stack, which clean room is compatible with it? If you have not started your first-party data collection, you may need to consider choosing your tech stack and clean room accordingly.
  • If you use the service of a network agency, which solution are they powered by? Most agencies have chosen a partner to power their media buys, it is worth checking with them. 
  • How competent is your current data science team in terms of leveraging the system? Clean rooms require specific efforts and their power needs technical skills to be properly unleashed.
  • Do not underestimate the legal aspects of data privacy and data sharing. It takes time and should be anticipated as part of all partners’ negotiations. 

There are multiple providers in the market who help to set up a data clean room and analyze the various requirements and options available. We are there for you if you need first-hand help.

What are distributed clean rooms?

“Distributed”, or “decentralized” clean rooms means that different partners keep their databases on different platforms without the need to migrate, share or centralize the data – it can still be analyzed in a seamless way. 

This concept is relatively new. For example, InfoSum lets advertisers load their CRM data into a personal “Bunker” whereas media owners can upload their addressable audience data into another “Bunker”. After that, multiple Bunkers can be virtually connected through anonymous mathematical representations, which enables audience matching and subsequent comparison of conversions to advertising exposure to attribute new conversions to specific channels and measure the efficiency of the campaign. 

Data Clean Rooms MMT
©Kim Heisler

Image based on Merkel’s graphic

This distributed setup, however, implies difficulties with governance and security and should be handled professionally.

What are the deficiencies of data clean rooms?

Most data clean rooms nowadays are still limited to one specific platform, which means marketers cannot gain a full picture of a customer’s journey or trace cross-platform attribution.

For example, the walled gardens only allow the use of their data on their own platform, thus forcing advertisers to focus their budgets on respective channels. But that may change in the future – and we will make sure we keep you posted. Stay tuned! 

Sources:

Special thanks to Lily T. who provided me with insider tips on clean rooms considerations.

Some data clean rooms are available on the market:

Cookie Life – Part 3: First-party data collection strategy

I wrote this article as part of a series published on the Mercury Media Technology GmbH blog.

Although most businesses sighed with relief after Google announced its intentions to stop supporting third-party cookies two years later than originally planned, the need to rethink advertising strategies is still there. The only difference is that the subject has now been reclassified from “urgent” to “important”.

Where large-scale targeted campaigns relying on third-party datasets were enabling both businesses and tech agents to make a fortune out of it, it is now time to adapt the digital marketing paradigm to the “new normal” and establish a first-party data approach. 

As explained in the latest article, relevance can be a powerful partner: firstly, because it helps exploit the “contextual environment” and secondly because it provides the opportunity to rely on the clientele and consumers already interested in your brand, products, or services. Capitalizing on those who are already interested in you can be extremely beneficial, as you can leverage the data collected from these people – upon their willful consent – to secure your future success. 

The Corona Pandemic has shown us that digitalization is not just necessary – it is essential to keep your company afloat. All digital spaces, both existing and newly created, can collect information about behaviors and conversion paths. Coupled with user identification, this information is unique to your business and it is a real gold mine. This requires collecting these data in a structured, secure, and exhaustive manner, employing an infrastructure capable of analyzing and using them properly. 

Welcome to first-party data strategy!

Content:

  • What can you possibly do with first-party data?
  • Why collect first-party data?
  • How to collect data?
  • How to set up first-party data collection?

What can you possibly do with first-party data?

“That is a good question!”. Why all this fuss? 

The last few years have made client recruiting so cheap that many brands have lost the habit of retaining their own customers. I remember often thinking in the 2010s, “loyalty does not pay anymore”. Brands stopped rewarding their buyers for “staying with them”. 

But yes, retention – or keeping your current customer happy – actually means creating value. 

  • Longer customer lifetime = higher customer lifetime value: your customer strategy can be evaluated in the long term, establishing the next sale and product upgrade cycle while keeping in touch with your customers. 
  • Lower cost of acquisition: building lasting relationships with customers instead of performing a series of one-off sales. 
  • Trust and advocacy/referral programs: leveraging this qualitative relationship to win new clients instead of purely relying on external factors. 
  • “En masse” personalization: defining customer clusters based on use cases may render one-on-one contact unnecessary since leveraging groups with similar tastes already offers a great personalization opportunity without extra costs.
First-party data collection strategy_MMT

Why collect first-party data?

Collecting first-party data can be a huge task if handled without a structured approach. There are so many potential data collection routes that it is important to establish business objectives and be clear on the status quo to kick things off: What do you wish to achieve with this new knowledge about your customers and prospects? 

Data strategy can be based on quite ambitious business goals but at the same time entail gradual development along with data maturity evolution in the organization. By launching this effort, your company will also avoid relying purely on external partners to achieve growth, such as walled gardens and third-party providers.

How to collect data?

There is no magic trick here: this effort would require collaboration across the entire organization: CRM, IT, Marketing and Sales will have to work together on this. It means not just an extra strategy layer – it is rather a change management project. 

  1. Assessment: What are the different owned contact environments where consumers and clients engage with your business? Is there any tech infrastructure in place to support information gathering, storage, and application? What are the current relationship platforms established with your clientele? Have you got a CRM system? Does it collect granular up-to-date information? 
  2. Defining the goals of your business behind this strategy.
  3. Providing the right tech base and expertise: it is not just about buying new SaaS solutions, but rather about creating the right combination of tools that will work together and connect you to external capacities. Internal staff also need to be engaged in the process and complete adequate training to ensure proper usage. 
    1. Consent Management Platform (CMP) to guarantee privacy alignment: align with global law + cross-platform and cross-device
    2. Storage and management => Customer Data Platform (CDP)must connect correctly with your marketing automation tools to be able to leverage the information stored.
    3. Data enrichment and usage: You may use a 2 or 3 step process to collect relevant client information like birthday date/gender or family status through prompt or loyalty programs in order to be even more relevant to them.
  4. Connection of your first-party data to external AdTech tools: we will explore this in a later article. 

How to set up first-party data collection?

1. Define a clear goal for your first-party data to make sure that you collect and store the right information to achieve it. The typical data to collect are the ones to help you understand what types of customers you have and how to maximize their lifetime value:

  1. Identifiers: “who” are your customers – emails, logins, postcodes, etc. 
  2. Interaction points with the brand (visit, referral, engagement, etc.).
  3. Transaction points (purchase, renewal, usage, etc.).

2. Build an approach to study and structure these customers into clusters that can later be leveraged for marketing purposes, e.g.:

  1. High-value customers,
  2. Frequent buyers,
  3. Abandoners,
  4. Brand ambassadors,
  5. Interested non-users.

3. Improve the relevance of your dataset via data enrichment campaigns using: 

  1. Login walls on the website,
  2. Registration in apps,
  3. Loyalty programs,
  4. Contests and surveys.

4. First-party data connection with external platforms: The data can now be connected to providers of identifiers matching outside of your universe to target the consumers not only in your own universe but also on partner platforms and extend the reach with the creation of “lookalike” audience in walled gardens media. 

5. First-party data connection with owned platforms:

  1. Sub-groups for personification at scale: give customers the feeling of being heard and understood. 
  2. Timely contact to renew or rebuy: take product cycle into consideration in parallel with transactional data to select the right message.
  3. Product suggestions and offers: create opportunities for cross-selling and upselling. 
  4. Active referral programs to win new customers. 

6. Reward your customers for entrusting you with their information: 

  1. Keep it safe.
  2. Identify clearly the benefits they get from sharing their data.
  3. Be transparent about the ways you will use this information. 

At MMT, we advise global companies around the topic of data usage, leverage that data to guide decision-making and establish data infrastructures. We help businesses to build their future growth through better insights into their media and advertising activities, including customer identifications. 

If you have any questions, do not hesitate to get in touch with us!

Sources:

Cookie Life – Part 2: Targeting without third-party cookie

I wrote this article as part of a series published on the Mercury Media Technology GmbH blog.

To follow up on the status quo on cookieless future, we would do our first dive on cookieless targeting as it offers an opportunity to launch very quickly.

We will give here a quick look into what are these targeting options. How to leverage it properly and why contextual is the trendy solution that all media agencies are talking about.

Which targeting relies on what? What is targeting? Which targeting is affected by third-party cookies?

Definition Targeting

Targeting means the precise addressing of target groups in online marketing. The most important prerequisite for this is determining the target group in advance of any advertising campaign. Advertisers have numerous options to target an online campaign precisely.

To go back to the status quo article, I mentioned different targeting options currently in use. Let’s clarify which ones will remain alternatives in the future framework.

MMT - Cookieless advertising - targeting option without cookies
  • SocioDemo: using sociological and/or demographic characteristics to target eg. Age group would be possible via Cohorts / FloC or opt-in data. We will cover it in part 3
  • Geolocation: relating to the use of lat-long positioning of the device use, this relies on realtime data that can be deactivated but do not rely on third-party cookie. 
  • Behavioural: privacy laws also aim at the capacity to follow users from one site to another. So this will be affected by the loss of third-party cookies. 
  • Time/season based: based on external circumstances- e.g connected to the weather forecast, time of the day, or temperature, it is not affected by cookies. 
  • Contextual: based on the content of the hosting page, this is not influenced by cookies. 

Why contextual targeting is (once again) cool?

The name is explicit – advertising in context – car insurance presented on a blog presenting car model reviews and comparisons. It is not new, we even used it before the internet existed! Yes, the print channel had Interest titles which was a great opportunity to talk to niche audiences. It is still used for specialized products like hobby groups or sport material aficionados. 

It emerged in digital advertising in the same way as an offering to help focus advertising based on interest, digitally, it requires to employ a technology which recognizes index or “read” the content of the page to analyze its content and allocated it to a “context” group.

Google Adsense (created in 2003 thanks to the acquisition of Applied Semantics) is a good example of the usage of contextual advertising solutions based on keyword-indexing. It has its detractors as it also created an enormous volume of sites uniquely design to attract Adsense ads by aggregating some other sites’ content on a topic, not bringing particular quality to the market. 

The main benefit of contextual advertising is relevance: there is no need of knowing who the person is if you just need to know what she wishes. It is based on real-time interest instead of past behavioral data analysis. It increases the chance of conversion when approached properly (let’s talk about next) as it focuses on the theme of the content and not the person reading it, It is offering an alternative to all companies which have not started collecting their own customer’s data (let’s talk about that too). 

How to leverage the targeting options that are not relying on cookies?

As said, Google pushed back the end of third-party and many marketers sighed with relief. It is just an opportunity to ensure we do not fall behind. There is no time to waste in starting to develop internal knowledge of the most efficient channels for your brand outside of this cookie world. 

One essential solution entails allocating a budget for a clear test and learn approach potentially using the SMART framework: Your general objective remains to understand which targeting is the most relevant to create awareness or convert to sales (as both are important to run on a long term focus) 

  1. Establish hypothesis
  2. Determine how you will measure success
  3. Define a time and budget limit
  4. Assess results 
  5. Share learning

To make your “test and learn” budget in contextual advertising a success.

  • Adapt the creative to a contextual environment, relating to the right topic assignment rather than the consumer-centric approach.
  • Monitor closely the performance of each context and associated creative to learn which are the best matches.
  • Internal factors can play a role in each activity, do not hesitate to use granular monitoring solutions to deep dive into your results when needed.

For context

The scalability of the campaign also depends on the quality of the contextual sorting. IAB has released a list of general categories on which website pages can be classified. It offers an opportunity for any publisher to list itself in a category of content, but this is still generic. In contrast, the niche of a context can end up impossible to scale as not enough content will be available. 

Good AI leverage Natural Language Processing (NLP) can now determine the sentiment of the pages which reduces the risk of brands being presented against non-relevant or offensive content. It avoids excluding entire categories out of fear of falling against the wrong news (e.g. breaking news section, user-generated content such as reviews and forums). There are good pre-bid solutions now starting to be integrated as part of the brand safety offer of adservers. Check your options. 

For other external factors

Build your company knowledge of the influence of external factors by approaching such categories with solid test & learn hypotheses and structure including the creative drawing a clear picture of this option for you. Depending on your service or product, the advertising can be tested on:

  • Location 
  • Weather 
  • Time of the day 
  • Period of the year

It is worth paying attention to these factors when running campaigns, it can save you cash by adding an extra relevance layer to your campaigns. 

To close

Remaining independent from large providers is a strategic decision to make, whereas it is always possible to choose to rely on a walled garden solution to provide the required data to leverage. No company should feel doomed to adhere to the technological limitations dictated by the market. 

Alternative targeting does not rely on third-party cookies can yield great performances once the understanding of the best approach is integrated. As it relies not on consumer-centric data, it requires assimilating a new mechanic and that implies testing. As long as Google offers time for that, there is not a second to waste in starting to build knowledge.

The next stop will be, first-party data collection and leverage, stay tuned.

Sources:

Cookie Life – Part 1: Status Quo

I wrote this article as part of a series published on the Mercury Media Technology GmbH blog.

Google announced at the beginning of July that it will postpone the launch of the Privacy Sandbox solution in Chrome to the “end of 2023” hence maintaining the support to third-party cookies. It gives the industry some air to implement their new strategies and arbitrage for future open-web campaigns. Let’s use this time to understand what is at stake. 

Why is scraping third-party cookies from Chrome bringing so much trouble to the advertising industry?

  1. Because Chrome represents 65% of all web navigation (cf. Gartner) and 75% of mobile ones (cf Visual capitalist). 
  2. Google alone attracted almost 31% of the total US ad revenue in 2019 (eMarketer)  (2020 being disturbed by Corona) across all formats (display, search, video- desktop, and mobile) and the revenue is growing.

Data collection and capacity to leverage it is becoming concentrated in the hands of a very few actors(such as Google, Facebook Group, and Amazon) due to the limitations that various data protection laws have triggered in the western world. 

To set the scene, let’s double-click on the context:

  • What is Data Privacy Protection?
  • What is classified as Personal Data?
  • What are advertising Cookies?
  • What is changing after the Elimination of Cookies?
  • What are the Alternatives to Cookies?

What is Data privacy protection?

Multiple examples of privacy laws around the world (non-exhaustive list):

  • The European Union General Data Protection Regulation (GDPR) in 2016
  • The Personal Information Protection and Electronic Documents Act (PIPEDA) in Canada in 2018
  • The General Data Protection Act (LGPD) in Brazil in 2018
  • The Data Protection Act in the United Kingdom in 2018
  • The Personal Data Protection Bill in India in 2019
  • The California Consumer Privacy Act (CCPA) in California (US) in 2019
  • The Protection of Personal Information Act (POPI) in South Africa in 2020
  • The Data Security Law in China in 2021
  • Various privacy laws in effect in Australia 

Something all these laws have in common is that:

  1. There are sensitive personal data that should be protected 
  2. Businesses can be held financially liable for the mishandling of data at different pipeline stages including secure processing, storage, and transfer (free or at a cost) 

Commonalities of data protection laws

Sensitive personal data should be protected. Businesses can be held financially liable for the mishandling of data at different pipeline stages including secure processing, storage, and transfer (free or at a cost).

What is classified as Personal Data?

Definitions vary from country to country, for example in Europe it says that personal data is any information that relates to an identified or identifiable living individual: 

  • Name and surname
  • Home address
  • Email address 
  • Identification card number
  • IP address
  • Advertising identifier of your phone
  • Health data which could be a symbol that uniquely identifies a person
  • Cookie-ID or location identifier

What are Cookies?

The identification cookies are files created by the websites you visit. They make your online experience easier by saving browsing information (the name or address of the site you visited, your ID, and timestamp). 

There are two types of cookies:

  1. First-party cookies are created when one visits a website. They are set by the site shown in the address bar.
  2. Third-party cookies are created by other sites that own ads or images on the visited website.

With technical cookies, sites can keep you signed in, remember your site preferences, and give you locally relevant content; such cookies do not require the user’s consent. 

Third-party cookies provide support to advertising targeting: they enable the selection of ads according to behavior as well as historical partners identifying user’s interests and potential needs.

First things first, let’s clarify what has happened to data collection via cookies:

Advertisers rely on cookies to track behaviors across the open web. Cookies help follow users from one site to another to serve them with ads that are coherent with their actions. At the same time, cookies record what the users have already seen for future reference (for example, for retargeting purposes).

Here is a timeline of the milestones on the path towards cookie eradication:

MMT - overview of advertising cookies evolution that affects targeting

What is changing after the Elimination of Cookies?

The elimination of cookies compromises the measurement of campaigns on the web and cross-device attribution. We are turning to a consented information gathering: cookies will be saved in the browser and will get no access to the user’s history of actions prior to sending an ad. Campaigns will be running “blind” without any historical information on users.

This entails the following:

  • It will incapacitate many actors involved in digital retargeting 
  • It will limit the ability to create lookalike and similar audiences based on collected first-party data 
  • Performance marketing activities, in general, are going to be handicapped
  • Lookalike and enhanced targeting will be limited 
  • Digital attribution models outside of walled gardens and cross-device targeting are going to be extremely limited.
For advertisersLosing the base for attribution hence no capacity to build conversion funnelsDecreasing cost efficiency of digital campaigns
For publishersLower ad revenue => need to find new sources of fundingConsent world for user identification
For Walled GardensMonopolization of the identification capacityNew sources of revenue
For Open Web data providersLosing the key source of revenue
For end-consumersLower ad relevanceLess intense ad stalking


What are the Alternatives to Cookies?

The whole market is trying to find the most efficient solution to overcome this challenge, with or without leveraging Google’s new offer:

  • First-party data, e.g. email addresses are back as the golden ticket to recognize users across devices and platforms and collect user data
  • Walled gardens will keep offering the same level of granularity in targeting, thanks to the user consent upon login and personal data processing agreements. They have developed network outreach => advertising offers outside of their walls.
  • Cookie alternatives like various technological solutions aiming to replace cookies are already either available or in development. We are planning to give you an overview of these in the next articles. 
  • More traditional targeting options including contextual advertising, geotargeting, seasonality, and timing can be leveraged to guarantee some sense of going back to classic tactics – brands can rely on the specialized websites and relevance of influencers to promote their brands to the users, pending on season, hours of the days and locations, thus limiting wastage. 

To close up

The topic is ongoing – it is important to grasp the context to understand what is coming and build a customized solution for each individual business. There is no one-size-fits-all approach, as business needs and target group behaviors are genuinely different from one sector to another. This series of articles aims to help you navigate through the changes – MMT is here to help you build your #futureproof data solution.

Sources:

Link to legislative documents:

How to really transition to data-driven decision-making?

I wrote this article as part of a series published on the Mercury Media Technology GmbH blog.

We have developed a guide for you to facilitate the planning of this high-potential transformation for your business. It addresses the most pressing questions that managers will have to cover to set out on this exciting journey:

  • What are data-driven solutions?
  • Why invest in data-driven solutions?
  • When to invest in data-driven solutions?
  • How to invest in data-driven solutions?
  • Which steps are needed to get started with the transition?
  • How to estimate the costs?

What are data-driven solutions?

Technical solutions which enable the handling and leveraging of data, aiming to improve business outcomes through transparency, cost-saving, and internal efficiency. Datasets could originate from various sources:

  • Internal: Supply Chain Management, Customer Service, Advertising, and so on
  • External: market data, competitors, legal environment, and other forces which can influence the company’s business.

The resulting outcomes can include production costs, sales, loyalty, retention, margin, average basket price, ROI… These solutions are named Data Science, Business Intelligence, Data Analytics and so forth. Their common point is that they are objective-based and drive tangible improvements enabled through data.

Why invest in data-driven solutions?

Because no business is capable of analyzing its data manually anymore. It is not only about collecting, organizing and presenting data but also about making sense of it and leveraging the analysis to reach the company’s goals.

Some companies may have implemented super powerful excel macros to convert part of their data into insights. But not to the fullest. Why?

  • Because The World Economic Forum estimates that by 2025, 463 exabytes of data will be created each day globally – that’s over 210 million DVDs per day! That means a LOT of data!
  • Because more data is being created while number crunching
  • Because number crunching is time-consuming, so decision-makers have to wait
  • Because manual solutions cannot encompass the full spectrum of data
  • Because companies cannot resort to a truncated view of their businesses

The pandemic exposed companies’ weaknesses in terms of anticipation and adaptability. The ones that have digitized show better ability to navigate and act in times of crisis. Do I really need to detail this further?

When to invest in data-driven solutions?

If the above “why’s” are not relevant, Companies may start a transition to the data-driven model for the following purposes:

  • Efficiency purposes: data-driven solutions provide analytical support for continuous improvement to drive a business towards its goals
  • Transparency and quality control: automation and centralized reporting help deter fraud and reduce human error which could generate great savings
  • Agility: a single source of truth at any given time reinforces the company’s capacity to decide quickly based on a clear common vision.

If you want to save on resources and energy as well as avoid unnecessary stress – then it’s about time to invest in data-driven solutions.

How to invest in data-driven solutions?

Transitioning to data-driven business decisions needs some preparation to guarantee success as well as quick internal take-up of the solution after the team onboarding (just like in any well-managed project, as my expert project management team member would confirm).

  • “I need a dashboard to keep an eye on everything”,
  • “Can you show me the performance results of the top 20 markets first thing tomorrow?”
  • “Can you send me this client’s sales volumes and commitments at the regional level over the last five years?”

Typical requests that we hear daily at work, requiring hours of manual work, which involves multiple contacts within the company, even on a global scale. In order to keep pace, the company needs a robust communication network.

Acquiring a BI SaaS license, purchasing a visualization suite or running a data analytics project will give you a fish, but it makes more sense to learn how to fish yourself: only a long-term solution will bring sustainable results.

5 Pillars to get started with transitioning

The transition to data-driven decision-making requires the following: Involving all management levels will help build the right momentum to make sure the project comes to fruition. To encourage the evolution of the decision-making process, the actual decision-makers need to feel comfortable with what is being brought to life (sounds like common sense, doesn’t it?)Data driven transition

1. Long-term objectives:

For this, it would have to start with a clear definition of the objectives to be achieved. It often requires an assessment of each department’s needs and future developments to visualize holistically the potential economy of scale and data synergies to be leveraged. 

While the list of objectives can be endless, the implementation timing and budget are always limited, but we will come to that.

2. Leaders of the data-driven transition:

How many people are going to be affected in their daily job? Is data-driven model implementation an IT project? Or a Finance one? Who is leading the transformation of the company?

This comes as a hurdle for many businesses: limiting the process to one department creates silos while involving everyone hinders decision-making. This is where external partners prove useful to handle multidisciplinary projects involving all stakeholders while keeping the focus on implementation timings and overall goals.

3. Enablement of the data-driven transition:

Do we contract an external partner or build an in-house infrastructure? Do we buy the servers or host them in the cloud? What are the requirements and restrictions of both alternatives?

It entails building a vision for long-term usage because it influences the scalability and agility that the system will require over time. This is an extremely important part of the process as it determines the financial scope of the project.

We will dedicate an article to the topic of structure and – we will link it to this section.

4. Timing:

There are few limits to what programming and machine learning can do – except being humans: these are rooted in urgency as we explained earlier in “Why focus on code quality in media and marketing software development?” article.

It’s essential to find the balance between complexity, scalability, and speed because needs will become more sophisticated as the data maturity of the organization grows.

There is no right or wrong answer to the debate whether to buy off-the-shelf or get a development team to build your proprietary solutions internally, it all depends on the objectives and ambitions of the business with respect to data. But you know: if you want to master driving a Ferrari at Le Mans, you may start training with a Skoda in a parking lot, but it is no use in the long run.

5. Roll-out plan:

Launching a new process across the entire organization and making everyone adapt overnight is truly a challenge – but it is not impossible. It requires good coordination and strong will as well as organized prep time: internal communication, training, test sessions and planned release to get the teams up to the challenge.

Launching sequentially (per region, per department, etc.) would generally take the same time, but organized into a series of smaller launch phases with shorter cycles. 

“Designing a roll-out plan including training, assessment, and iteration phase at each step of the process will secure higher efficiency and company take-up.”

Aiko Müller
Director Implementation & Support, MMT

How to estimate the cost?

As a starting point: the basic calculation deducts the resource savings (man-hours saved on reporting/data gathering or number crunching) from the solution costs (which would usually be a SaaS license).

The costs of designing, building and implementing a more sophisticated data-driven solution have to be visualized in the long run as benefits and needs will evolve along with data maturity.

The benefits of transitioning to data-driven processes are ranging from faster reporting, more transparent decision making and information sharing, to better cost control and resource allocation. It can boost the agility of future business decision-making but it will not happen overnight.

This could be enough to start exploring investments in many basic data-driven solutions but it would be shortsighted to limit the calculation to this, as the cost of data-driven decision-making is 4-fold – all offering the choice between internal and external resources:

  • Cost of data: the gathering (data connexion and provision) and storing it (servers or cloud infrastructure and its maintenance)
  • Cost of resources: IT (for servers), data engineering (for cloud computing and provisioning), data analysts (for modelling and visualization), business intelligence (for insights)
  • Cost of implementation: setting up the team, training and follow-ups, support and knowledge base management => without forgetting the time that teams need to invest into the training and usage learning
  • Cost of change management support: to guarantee successful implementation, it is important to monitor the changes and push innovations forward. Such investments can be an absolute waste of money when no assistance is provided to the people who have to make their practices evolve. Change management is what would actually achieve data maturity across the organization

Then the nature of savings:

  • Resources savings: FTE spend on collecting, preparing and visualizing data that now can be automated; reporting preparation (internally or across suppliers)
  • Company savings: that real-time decision making has allowed
  • Efficiencies: in the company operations and supply-chain that data maturity offers.

Conclusion

As we love to call it, the disruptive aspect of data in our world is so mind-blowing that companies have difficulty comprehending it, sometimes even reluctant to accept it. The reason often originates from the risk-averse leaders who foresee disruption as a potential negative impact on the business in the short run and would rather let the next senior team take the plunge, and keep their own legacy protected.

Sometimes disruption is just too much, and transition offers a “safer” – more acceptable – perspective to those risk-averse managers. It creates the potential for learning and growing with the new approach given the necessary time for the team to reach mastery and become more comfortable with the new practices. That is why “change” is to be managed and not enforced, it brings stronger business benefits over time.

Data infrastructure for advertising – where to start?

I wrote this post for MMT

Transitioning to data-driven marketing, which has become a must-do for business performance in the last 5 years, is not uniquely a mindset to adopt.

Using efficient data for decision making is not about building data-heavy graphs in business presentations to help you determine your next business steps. You need an infrastructure setup to collect those data sets but also to compile and often visualize the data in dashboards so that you can leverage it. You need to be able to obtain, organize and read the relevant data so that you can make smarter business decisions.

Manual preparation of reports and data can be time consuming and resource heavy, which can lead to duplication and errors that can easily be overcome by automating fetching flows and updates. 

Table of content:

Is there a specific issue to data collection in the advertising industry?

From the beginning of the media digitalization era, each individual publisher and service provider has done its best to keep up with technological developments on the market. However, the industry at large has not managed to set standard processes for buying and delivering media (some countries have independently created a standardized approach, but this is not the norm). The absence of standards makes it challenging to find fast and unique data flow connection solutions that work for everyone. Marketing teams, wishing to get a clear view of their media activities, have to individually connect the data from the necessary platforms like social media, programmatic, DMPs, publishers, TV booking systems, etc.

How do you connect data flows?

Solution 1: Third-party provider

Some companies have made it their mission to help marketing teams easily get these connections by acting as a third-party service provider. They have developed adapted solutions that deliver formatted data to their client’s warehouse (or theirs if their client does not have one) where they organize the data. This has made connecting data provision fast and resulting in quick launch times for data-driven projects, offering speed and simplicity at a cost. If businesses do not have the team or the experience needed to build the data infrastructure necessary to run their own solution, these providers can be extremely helpful. 

This connection still needs to be leveraged through an additional visualization solution, as the connection system does not include a direct interface to “read” what it has extracted. What’s more, the meta-connectors do not offer ad-hoc offers, and small businesses end up paying for a more complex service that they do not need.

This also deprives marketers of transparency regarding data delivery and control as it means being dependent on the provider’s ability to offer the required connection and regular updates no matter what happens and because update issues that may arise are not always anticipated (e.g. the database does not update properly the day you have the largest budget presentation of the year).

Positive: Data connection is made fast and easy to a very large number of partners. API speaks directly to your applications.
Negative: This can lead to a lack of transparency and flexibility on a couple different fronts: data-availability (when new data is ready to be consumed) & troubleshooting. No savings possible: You pay for a Ferrari when you need a Fiat.


Solution 2: API connection

Modern platforms mostly offer API access to catch this data – API being the layer of software which allows communication with another application – to allow data extraction at regular times and maintain an updated database. Some make it possible to generate data ingestion as well, which makes it possible to create a centralized self-service solution that can give commands as well as receive information.

But again, API is built into the code of an application and does not follow a particular standard in the marketing industry, which forces businesses to address these connections one by one in order to obtain their own data. Connecting to some of these APIs is extremely challenging. Only veteran engineers can code a working connection and manage to fetch the relevant data.

On the positive side, APIs offer transparency and control over the data flow and engineers can quickly resolve issues and troubleshoot connections if anything happens.

Positive: Provides direct contact to your dataflow from a particular platform with control and transparency.
Negative: Requires qualified engineers to connect and maintain your connections to your application. It embeds the API in your application => which means that your application has an API too.

Solution 3: RPA

Robotic process automation (RPA) is a surface level automation software that can be used to allow applications to talk to each other.

For those who haven’t yet incorporated a dedicated protocol for data sharing, human actions can be “mimicked” with a piece of program that retrieves the necessary information. This is called robotic process automation, or RPA, and once coded it can perform tasks the human hand would perform otherwise, like basic chatbot solutions or a report generator on a platform UI. It is a simple piece of automation, not an AI, and performs repetitive tasks like copy and paste, logging to applications, scrapping data and making a calculator very well. It is fast to implement and does not affect the structure of any of your software applications, which keeps it from disrupting everything that is already in place. However, it can easily crash or underperform of there is a disruption of the environment. A basic RPA can only deal with the keyword it knows and will not identify spelling mistakes. However, it would be a perfect way to update a database when using forms to fill dropdown menus and ticked boxes.

Positive: RPA is a good solution for fetching data when no API is available. It is cost-efficient and can be an effective way to replace repetitive human tasks, thereby reducing potential human errors.
Negative: RPA does not determine whether the task has been well-executed. It can only rely on preformatted information to guarantee quality results.

Next steps

At MMT, we have studied the connectors available on the market, and our team is able to interact with API as well as write RPA. We adapt our client offers to the most relevant solutions for them, their business, their needs, both long term and short term. Get in touch with us for more details.

Sources: 

Why scaling beyond walled gardens?

I wrote this post on MMT

Walled gardens offer an amazing platform to get brand presence quickly to the market, targeting core audiences for what seems a fraction of the budget. They have become into an essential tool for building awareness to the point of overspending other digital channels and most other media channels in many countries in the course of the past 10 years. But what then? Why scale out? Read on to find out the why and the how-to kick-start your company’s ‘scaling out’ for success.

Questions this article answers:

What are walled gardens?

Definition Walled gardens Walled gardens are closed platforms requiring a login to access data. They are able to track every single detail of user activity within their universe without having to share details with users or advertisers. This is the first-party universe: information on users is constantly collected, consent is given by subscribing and accepting of terms of use.

The different walled garden platforms offer 24/7 content service skewed towards the users’ assumed desires and served through a platform designed to maximize time spent. The most famous ones are:

  • Facebook groups (Facebook, Instagram)
  • Google (Youtube)
  • Amazon (marketplace, Prime, Music)
  • Apple (TV, Music and Apps)
  • Tencent (QQ, Qzone, Weibo)
  • Twitter
  • Linkedin
  • Twitch
  • TikTok
  • Pinterest
  • Snapchat

Facebook and Google account for over 50% of digital advertising spend worldwide.

What are the benefits of using walled garden advertising?

Thanks to the close universe they created, walled gardens provide a precise set of targeting opportunities not only based on location and time but also on behaviors and tastes. They can also guarantee deduplicated cross-device advertising, as they rely on a login solution to address users across all their connections.

Walled gardens provide a controlled environment for advertisers, giving confidence that is safe from conflict, violence and horror stories. They also highly qualify the indicated target audiences and geographical areas when configured properly.

They are still the most mature alternative to cookieless advertising of those solutions expected to hit the market in the next 12 months or so (with changes to Safari ITP, Firefox ETP and Google Chrome to come in 2022

What are the problems with walled gardens advertising?

Walled gardens do not share data with their customers. They report aggregate information on campaign engagement and performance without being transparent in regard to the campaign’s global advertising visibility, which prevents advertisers from acquiring deeper knowledge about what works and leveraging information to help them save on spending via the details on algorithm selection.

That means that any effort to learn from walled garden activities and mechanics cannot be applied to other solutions, as usage differs on top of the provided campaign results.

Time spent on walled gardens is not aligned with advertising spending. Walled gardens represent less than 40% of the time spent online in the US, according to Openx, and 40% in the UK, according to WARC. Statista reports walled gardens at 27% of daily social media usage in Germany in 2019. Despite this data, Facebook, Google and Amazon attracted 67.9% of ad revenues in the US in 2019, according to eMarketer, these platforms being based on user-generated content by nature (Amazon TV claiming a limited share at 6.8% of total company revenue). 

Why should brands that wish to grow not to limit themselves to walled gardens?


“Consumers are always looking for the next thing. So, our ability to scale audiences with any single partner and expect that we’re connecting with them throughout their entire journey, or all the way from the top to the bottom of the funnel and purchase, would be shortsighted if we only looked at one particular partner.”

Sean Peters
Chief Strategy Officer, Publicis Media

The old saying, ‘Don’t put all your eggs in one basket,’ is true. No social media has the capacity to fully scale up in every context and for all sectors, geographies and product cycles.

In the 1950s there was only one TV channel, which was fine back then. In today’s scattered offering, communication needs to be agile, relevant and smart in order to reach consumers with real impact, which includes not limiting your efforts to one platform.

Where are the media opportunities outside of walled gardens?

Broadening media selection in advertising activity can quickly become costly, as it requires producing creative content adapted to the other forms of media, objectives and universe chosen.

Digital media

The first, and most cost-efficient, step is to stick to digital advertising in the open web. That means websites and apps that exist outside of walled gardens. These represent over 50% of the time spent and benefit from a higher level of trust with the public.

IT offers a variety of buying mechanisms through programmatic solutions using third and first-party data for content outreach, contextual and publisher deals. The advantage here is that these use standard creative formats that don’t require further adaptation. The level of content and quality of environment differs greatly (as is the case with social media), but providers offer impression-level transparency and technical cost visibility to facilitate result tracking.

TV campaigns

The most powerful, and potentially expensive, is TV (linear, connected [link to Advance TV Article] and on-demand) as this format makes it possible to build advertising reach more rapidly. This used to mean straightforward buying of a few national channels offering powerful campaigns, leveraging expensive TV spot productions to generate leading campaigns that were then used for a few years. Today, TV is more scattered.

TV still represents the highest possible reach in the western world (94.1%of the UK population watches TV every week). Today’s consumer might watch sports and news on live television, dramas on subscription VOD and comedies through OTT. The implication of all this for marketers is that there are three key variables that need to be taken into consideration when building a plan: content, data and viewing platform. This means the creation of programmatic TV buy offers that combine these in a multiscreen plan.

Out-Of-Home (OOH)

Urban areas have seen the volume of digital opportunities to advertise in the streets growing. Considering new options to use media while on the go, OOH represents a good opportunity to target a younger audience that is more curious and willing to try out new things.

Cost of production is not high. Advertising campaign scale with time as the frequency is higher (once normal travel conditions have been restored) and new measurement technologies offer quality tracking solutions. As for TV, digital OOH (mostly urban areas) can be bought in programmatic platforms.

Radio and audio

Audio has been experiencing a transformation with the emergence of the podcast industry. (According to the infinite Dial, 37% of Americans listen to podcasts on a monthly basis.)

The development of digital radio and streaming have made music more accessible and digital audio extremely popular. As for other types of media, these can be bought on programmatic platforms.

Radio and audio are generally the cost-effective media of choice for traffic campaigns and low-cost reach, as they offer a great opportunity for brands to reach loyal listeners regularly. They also benefit from relatively cheap advertising production costs and quick turnaround. The efficiency of the media has long been proven by footfall measurements and regional testing.

Print (paper and digital titles) or publishing houses

Whilst Paper has been slowly on its way out over the past three decades, there are pockets of offerings that present valuable opportunities in a cookieless future:

A resurgence of specialized titles focusing on niche hobby and segmented content offers a no-wastage option to many consumer goods that attract offline customers

Contextual opportunities to address potential clients and build awareness in an expert environment while leveraging the trust established by the publishing provider

The quality of the associated content, which can attract a higher revenue crowd and generate a higher basket price for the same acquisition cost

We will be creating a series that will cover each type of media in 2021 and look at the benefits and constraints of each in more detail. Subscribe and stay tuned.

How can MMT help?

At MMT, our data analytics team supports your business needs when it comes to budget allocation and media efficiency based on market and client data. Whatever your business objectives, MMT defines the most relevant media mix that will move your business impact forward and scale up your business.

Our MMT Mercury media management software helps advertisers and agencies manage their digital campaigns end-to-end from planning to invoicing, including trafficking and monitoring across all platforms, walled gardens and the open web, connected TV, digital OOH, audio and digital print.

MMT Scout will help you visualize your performance and make faster decisions without spending hours gathering insight on multiple platforms. 

Other reads :

AdAge 0 Shares

What 2021 can bring?

I wrote this post for MMT

Looking back at all that we learned in 2020, we have many opportunities to make 2021 a year of success. It is clear that the acceleration of digitalization, specifically in the first half of the year, will continue in all branches and across all company activities. But how can we exercise our risk-averse muscles to help us avoid trouble while tapping new pockets of growth?

Table of content

Teams

What began during the crisis may become the norm. #WFH forever? How do you integrate new resources into your team?

  1. Read the signs – Although teams were happy to have more flexibility, they might be feeling lonely now that time has passed. When the second wave of lockdowns hit, people had to go back to working at their kitchen tables. Still, a general feeling of benefiting from the situation is emerging: less stress and more focus combined with stable productivity. Skilled workers and introverts appear to be benefiting the most. As a company, it is important to survey the feelings and needs of your team members in order to be able to create an effective post-Covid work environment.
  2. Encourage diversity and belonging – Integration means more than just hitting the figures. Taking steps to guarantee equality and mutual respect also means taking differences into account by considering everything from refraining from setting up meetings at dinner time to celebrating all religious events and being considerate of time differences by rotating regular meeting times. There are many ways to show people respect. The basics include empathy and understanding without judging aspects of life that do not impact efficiency at work.
  3. Create inclusive training practices – New context, new needs: You can improve efficiency by training people towards the new normal. Doing this may mean establishing a completely new set of training practices, edging away from teleconference etiquette and turning toward collaborative tool usage as well as structuring projects and standard operations. The objective is to provide comfort in times of uncertainty by enabling your team to build the skill set that will help them feel capable while #WFH.

Managers

From managing uncertainty to managing digitally?

  1. Build structure into remote teamwork – Office space is organized to provide good working conditions for all employees. Country regulations see to that by requiring good quality office materials, lighting and air. At home, employees are not always equipped to maintain these standards. This may be fine for a couple of weeks but not for the long term. Reducing your office space does not mean that your employees should have to bear the burden of providing equipment, access and training. Going the extra mile can even include encouraging health practices like regular gym time options.
  2. Create feedback spaces – One significant hurdle that comes with remote working is the lack of management contacts and informal feedback opportunities. Although both senior and mid-level employees are used to some autonomy, engagement is correlated to management relations. Digital managers need to build up their feedback arsenal so that they do not lose their teams.
  3. Limit repetition and misunderstandings – Teams that are basically living at their workplace need to be clear on tasks, processes and updates. It is extremely tiring to attend stand-up and update meetings where you hear the same news but are not always given clear next steps and responsibilities. Avoid multiple update loops by centralizing history logs within workflow platforms and chat tools and instill in your team the advantages of using collaborative documents and flows in order to limit friction over individual to-do lists.

Business & Marketing

How to perform in the “new normal” and creating value from headwinds? 

  1. Break team silos by centralizing data infrastructure – Offering an infrastructure where teams have access to the data they need without duplication makes it possible to combine their data in order to gain transparency. It also reduces the amount of necessary reporting and prevents duplication, which saves time and reduces errors for teams, giving them more time for exchange and thinking.
  2. Generate margins by increasing the productivity of each team member – Every team member has an idea of how to improve their own productivity, even if not every idea can be applied on a large scale. Asking your team for solutions bottom-up reveals the approach you need to take toward work improvement => everyone can contribute their tips and tricks for boosting productivity.
  3. Use data to build your performance assessment – Giving your team access to automated dashboards and data knowledge can open doors to better performance. By instilling healthy KPI-setting processes, each team is able to clearly visualize expectations and results without extra work. 

Extra Steps

How to strengthen your advertising?

  1. Improve your advertising process pipeline – You can take advantage of tremendous opportunities when it comes to saving time and resources, from in-housing part or all of your media to managing vendor relationships and yearly commitments. Data can be used to identify room for improvement.
  2. Leverage your “everyday experts” channels – Influencers have gained traction in this digital age. The end consumer is attracted to audio and video formats for practical reasons, which opens up an enormous opportunity for new content development. Be the authority in your field
  3. Loyalty and advocacy are even more central – Acquisition is at the heart of many advertising strategies. However, customer retention is an important money-saving opportunity that can increase your bottom line. The full funnel for customer experience brings with it opportunities to expand your clientele.

Summary

Data can be an enormous help when it comes to building and monitoring a “new normal” structure. At MMT, we provide the support you need to design and build the relevant workflow, dashboards and data pipelines to increase your advertising productivity and help you build your new normal. Get in touch. How to perform in the “new normal” and creating value from headwinds?