In my experience as an Adobe Audience Manager consultant, I have noticed that many clients need a lot of hand-holding at the beginning when working with this DMP. Coming from the Web analytics world, this was a bit of a surprise to me at the beginning. I remember when I started an Adobe Analytics project I worked on 6 months ago, one of the client teams had a spreadsheet with 138 requirements… and that was only one of the teams involved. They knew exactly what they needed from the tool, which made my life easier. However, this is rarely the case in an AAM project.
In order to get some quick wins, we recommend to start with the low-hanging fruits. For your first few campaigns, do not try to create very complex rules for segments. Instead, think about easy rules that only require online behaviour. Here are a few of them:
- Exclude customers from prospecting campaigns. This is probably the easiest case and the one that makes most sense: stop showing prospecting ads to users that are already customers; you are 99% sure they are not going to convert. This is as simple as creating a segment with customers and send it to the DSPs. Then, using the exclusion capabilities of the DSPs, exclude the visitors in that segments from the prospecting campaign. One of my customers had a drop of about 20% in the cost per acquisition just using this technique. If you use AAM with Adobe Analytics, here you have a few examples of the traits you can use to detect that a visitor is a customer:
- The log-in event has been fired: (c_events contains “eventX”)
- If you are capturing the CRM ID in an eVar or prop, then something as simple as (c_evarX/c_propY matchesregex “.+”) should do the trick
- Any page of the private section (e.g. c_pagename == “my:private:area”)
- Depending on what you sell, it can be as simple as users who have purchased something: (c_events contains “purchase”)
- Include only local visitors or exclude non-local visitors. Very similar to the previous case, if you have a business that only sells locally, you do not want to waste any money on banners shown to visitors that come form regions where you are not going to delivery your goods. In AAM, this is very easy with geotargeting with platform-level keys.
- Retargeting abandoned baskets. For all of those products that provide you with a high margin, you can create segments with users who have abandoned the basket with those products in it. You then create very specific retargeting campaigns using these segments. The segments will formed of two traits: “Add to basket – <product id>” AND NOT “Purchase – <product id>”
- Add to basket: (c_events contains “scAdd” AND c_products contains <product id>)
- Purchase: (c_events contains “purchase” AND c_products contains <product id>)
- Up-sell or cross-sell. Target customers that have recently purchased certain products, customers who your experience (or your Web analytics data) shows that they are very likely to convert again. This is as simple as the previous example: (c_events contains “purchase” AND c_products contains <product id>)
- Frequency capping. If a user has seen a campaign more than X number of times, stop showing the campaign to him. You need to decide which is the optimal X, but we all know that after a certain amount of times, if the user has not clicked on a banner, it is very unlikely that he will do it in the future. In AAM, you would use the frequency and recency capability of the segment builder.
What do you think about these initial segments? Any other segments you would recommend as low-hanging fruits?