Attribution models for mobile advertising

A well-built media plan involves the very difficult challenge of trying to balance the different advertising channels used in acquiring and retaining a customer, and attributing the right merit to each of those channels to achieve a sustainable and scalable customer strategy. Therein lies the challenge: knowing the real contribution made by each channel, the value from the advertising spends invested and what attribution models to use.

The promise of “measurability” of digital marketing has led many to believe that the problem could be greatly simplified. This is partly true. The incredible power to measure digital channels has made it possible to find better solutions to the media planning process. However, over-simplistic approaches (where numbers replace reasoning) may achieve the opposite result of what was intended.

A simplistic (and in our view, wrong) approach to solving this complex challenge, is to try different channels simultaneously, measure them all with the same last-click attribution model, and keep eliminating those with the worse last-click as measured by CPA results.

The benefit of this method is its extraordinary simplicity. The problem is that it may achieve the opposite of what we want.

Measuring the sales funnel with different attribution models

Going back to marketing basics (the AIDA [Awareness, Interest, Desire, Action] framework is probably a good common reference to use): acquiring a user always follows a sales-funnel approach where we prospect potential leads at the top of the funnel (Awareness), find those that are interested in our product (Interest), follow them through the decision process (Desire), and finally convert leads into buying customers (Action),at the bottom of our funnel.

Each of these steps in the sales funnel has different objectives, and hence, can’t be measured equally. The objective of the prospecting phase is to make people aware of a product (top of the funnel), so that eventually, the lead will become interested enough progress through the sales funnel and end up buying. We can’t compare the cost of acquiring a new user to the cost of acquiring a user that is familiar with a product already (bottom of the funnel) and is ready to purchase.

If we do make the mistake of comparing these costs equally, we will tend to believe that the tool or channel that was helping us convert a lead at the bottom of the sales funnel is always better that the tool that helped build awareness to a new lead at the top of the funnel.

The catch is that if we follow the simple strategy defined above, and end up only with bottom of the funnel channels and tools, we will get very good CPA metrics, but very low scale. Indeed, once everyone that knows our products (those leads at the bottom of the sales funnel) are acquired, there’s no one else to convert.

This is typical of poorly designed media plans. It’s easier to quickly eliminate those channels that help us drive product awareness and end up with bottom-of-the-funnel tools such as search and retargeting channels that have great CPAs. The problem arises when we try to get scale. It’s then that we start pouring money into these channels and when CPAs become worse

The real key to the very complex problem of designing the perfect media plan, is not only which channels to use, but also how to attribute merit to each channel to measure the effectiveness of each with respect to the distinct goal that should be attributed to each acquisition stage.

That’s where programmatic buying can play a significant role, smartly utilizing its data processing capabilities to efficiently achieve properly measured results at each stage of the funnel, in conjunction with other marketing channels.

Ideally, last-click attribution should only be used to measure effectiveness of bottom of the funnel channels (search, retargeting). View or algorithmic attribution should be used to attribute merit and measure effectiveness of top-middle funnel channels, like programmatic.

The idea is to be able to measure “awareness” in a way that allows marketers to choose the right platforms without compromising scale and efficiency of a campaign. This measurement is possible. We should look into measuring which of the leads that arrived to the bottom of the funnel were impacted by top of the funnel channels.

For example, If I impact one million people with my awareness campaign, I should make sure that the 5,000 people that end up converting were among that million impacted a priori.

Properly combining channels, with the right measurements and attribution logics, one can achieve the holy grail of a scalable and effective marketing strategy.

Pre-bid for brand safety and viewability

Smadex takes brand safety very seriously: this is reflected in our platform, by giving advertisers full transparency into bid-stream level data via real-time reporting and with our partnership with Integral Ad Science (IAS).

We are excited to announce our pre-bid solution using IAS for viewability, brand safety and fraud. Pre-bid is an industry best practice approach that’s now widely accepted. For example, it predicts viewability in real-time before spending on an ad placement. The technology for pre-bid is provided by independent third party vendors like IAS, that make sure an ad is seen or placed in a safe environment.

Benefits of pre-bid

An important point to note is that the benefits of pre-bid are maximised when combined with programmatic; real-time decisioning, transparency of placements, more viewable ads, increased campaign performance, efficiency and effectiveness and overall higher quality campaigns.

Give the current industry concerns about viewabilty, brand safety and fraud, pre-bid provides a level of guarantee about ad placements. Ad spaces are only bid on and served if the ad inventory meets the specific conditions set by the advertisers in the pre-bid filtering.

How does pre-bid work

Advertisers must specify their pre-bid requirements upfront: viewability thresholds up to 70%, brand safety exclusions, suspicious activity levels, contextual targeting and languages. Some of these filters can be combined together such as viewability plus brand safety.

Advertisers can play with the IAS pre-bid solution by clicking on the Audiences > Prebid audiences in the global navigation. Reports are generated and available via the Smadex IAS account and our operations team will be able to send advertisers regular reports on campaign activity.

One of the recognised downsides and trade-offs that advertisers need to make when considering using pre-bid is the impact on campaign delivery. This trade-off can be managed by changing thresholds such as viewability levels. Another point to note is that there are limitations with pre-bid and in-app advertising; the in-app versus mobile web pre-bid options are visible in the platform and advertisers.

Screenshot of the pre-bid interface in the Smadex platform



For more information about running your campaigns using pre-bid contact sales[at]smadex[dot]com.

Adding footfall attribution to measure impact of location campaigns

We are excited to announce that we are offering adsquare’s Insights solution to measure and attribute the impact of location-based campaigns to footfall. adsquare is a mobile-first data exchange, bringing together advertisers and data providers in a fair, secure and privacy-friendly.

For those of you new to this topic, the purpose of footfall attribution analysis is to determine that age-old question: Did my marketing spend work?

When advertisers spend on digital media, mobile metrics alone are not enough and they need to understand what has been successful at driving consumers into a store; this is where football attribution provides answers. (Note: Footfall is a retail marketing term used to describe the counting of people that enter a store.)

A footfall attribution study monitors each of the locations targeted during a campaign and analyses users that have been exposed to mobile ads against a control group that has not. The study generates insights and analysis in the following areas: audience analysis, temporal analysis, top stores and competitive analysis.

The important KPI generated is uplift: measuring the impact of mobile ad exposure at driving store visits, determined by comparing those exposed to the ad against those who were not (control group).

Once a location-based campaign has ended, Smadex will send data securely to adsquare for processing and analysis. The study will take a number of weeks to complete.

Smadex’s powerful geo-location tools

Our geo-location option can be found in the work space area, located on the global navigation tab. Advertisers build their geo-location lists and targeting once, save it, and then they can use this list as many times as needed in multiple lines.

To create geo-location targeting, advertisers can either upload a list of latitude longitude coordinates or addresses with zip code (we can support tens of thousands of locations), or individually plot the locations on a map by dropping a pin. Advertisers can create and manage any number of geo-location lists and edit a list at any time. Advertisers can choose the radius for each location within a line.

Smadex’s geo-targeting interface

Footfall Attribution

Footfall Attribution

For more information about running a location-based campaign to drive store visits contact sales[at]smadex[dot]com.

For more information about adsquare’s Location Attribution and Insights Study, contact sales[at]adsquare[dot]com.

Retargeting users based on real-time campaign behaviour

We’ve recently released a new retargeting feature in our self-service platform under the Audiences tab, called Activity Audiences. This new feature enables advertisers to generate new audience segments in real-time, based on campaign events such as banner views, clicks and video views. For advertisers, this is a very, very powerful feature.

Data capture

For the first time, advertisers will be able to create custom audience segments based on specific in campaign events that they are interested in and generate those new segments in real-time as the campaign is running. These new segments are stored in the Smadex DMP.

For example, with a video campaign, advertisers will be able to create a segment of users that have been exposed to the ad and watched the video for 30 seconds. This is extremely powerful and clearly underlines the value of digital and mobile.

Moreover, this data has enormous value and potential for smart advertisers: simply knowing what users have been exposed to your 30 second commercial means a) you know what consumers have been exposed to your brand, b) there is a general awareness about your offering and c) enables retargeting or lower level sales funnel activities.


Retargeting in this context is about reconnecting with users based on specific in-campaign events and applying different treatment strategies.

For example, let’s say that you are the planner at a global brand and you have just run a mobile video campaign via Smadex to extend your audience reach in the UK with hard to reach Generation Z. This segment spends most of their time with their mobile phones.

Having the capability to generate a gen_z_completed_video_view_30_second segment would enable you as the planner to tap into this audience again with follow on treatment strategies. One example could be a geo-location campaign using full screen ads for strong branding and messaging to drive in store visits after being exposed to the video ad.

Furthermore, advertisers can overlay third party data sets from Factual, Adsquare or Weve and provide an additional layer of filtering for improved campaign targeting.


The new Activity Audiences are private and only viewable and accessible by advertisers via their Smadex accounts. Advertisers will be able reuse these segments at later dates and across different campaigns.

Screen shot of the Activity Audiences feature:


Smadex platform

Smadex platform

For more information about using Activity audiences, contact sales[at]smadex[dot]com.