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Audience manager

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A system for marketers to create targetable audience  groups through slice and dice of customer data.

Note : To comply with my non-disclosure agreement, I have omitted and obfuscated confidential information in this case study.


The goal of this project was to design the Audience Manager. Audience manager is the part of Capillary’s Product Suite and will be used for creating and managing audience lists. These lists are created from the brands existing users base to create highly relevant marketing campaigns. There are two ways to create these list either you upload a list or create one using predefined rules set. 


Solo designer


9 months



  • Lists were restricted for use in Campaign Manager. No way to use them in other products.

  • Lists were not available for use outside of the campaign in which it was created. There was no way to reuse lists even if the same customers are targeted at different times


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I had multiple user research sessions. These sessions were split between telephonic conversations and in-person interviews. The goal of this process was to understand their needs, goals, challenges with the current system and expectation from the new system.

Key issues that users pointed out are

 1   Users were not allowed to Edit or modify an existing list.

2   The older system was slow, took a lot of time to process a list.

3   Predefined rules were confusing, were not giving the expected result.

4   Reachability numbers were not available while creation, though it played an important role in decision making.

5   Users were using segmentation because list lacked flexibility.

  No way to reuse the list in another campaign, as the list was created under a campaign.

7   Users wanted to use these lists in other products, which was not allowed.

To understand the user's needs I looked at similar products. These are the few tools that I evaluated Mixpanel-segmentation, Google double click, WebEngage. 


Heuristic evaluation:

I also conducted the heuristic evaluation and usability testing of the current system to identify high-level issues

1   Visual indications for actions being performed are missing. Feedback or indication of a pending action (say 

     processing) was missing, which resulted in confusion & irritation for the users.

2   Proper alignment and design consistency were not followed across the interface.

3   Filter labels do not correspond with user terminology/mental model.

4   Primary actions and flow not clear



Few interesting insight that I derived from the data I collected during research.


 1   I asked the tech team to retrieve last 2 years data on how lists were created and what parameters

were used for creating these lists. After looking at the data I realised the most of the lists were created by

using upload options.


2   After looking at the data I also realised that the users were using the same set of filters most of the times.

3   Basic flexibility such as ‘OR’ between conditions was missing. In a lot of scenarios, users wanted to do an

OR between conditions, but the system didn’t have that option. Users were creating 2 lists and then merging

them into one.

4   There was a good number of cases where users wanted to target the same set of users but since that

was not possible, they were exporting the list from one campaign to upload in another.


5   Since lists were only available in the campaign manager, users were creating segments to use in other products


6   In some cases, the predefined filter labels were misleading. In some filters, the mentioned date was

included, whereas it was not in the rest. This did not inspire confidence.


7   During list creation, users look for audience level data such as reachable customers and demographic

wise distribution, as it helps make the targeting more effective.


Based on these insights, I realised that there will be 2 types of users

          1.  Account managers

      The ones who will be consuming the content


2.  Analytics team

      The ones who will be creating the content and sending it to the account managers.



Based on the user research and insights, my primary objective was to resolve these problems.

#1.  How to introduce complex filter conditions:

Quite a few brands were using very complex filter conditions while creating their list, but the usage wasn't

that high. The first approach was to define all the possible filter condition, but this will result in too many filters.

Users will ask for new filters now and them, which will unnecessarily make the filters list cluttered. The second defines basic filters and in each filter give few optional fields for advanced filtering. This will solve most of the scenarios with minimum no of filters.

       Basic filter

       Advanced  filter







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#2.  Information architecture choice:

Audience groups will be consumed in the Campaigns and Loyalty systems for precise and personalized

targeting. They will also be used in the Reporting product for further analysis. In the future, I wanted to allow

list creation from within this product, as most analysis is anyways done there. So the question here was that

where will audience manager reside. The first approach was to keep it under Campaigns, but Analytics

associates do not have access to it. So, they’ll have to pass on the information or the finished lists to Account managers. The whole process feels bit complex and lengthy. The second approach was to keep it under the Reporting product, but in that case, Account Managers will always have to depend on the Analytics team to

create the list, which is not a good idea. The third approach was to keep it in the shared repository, where both users will have access.

#3.  Filters rewriting the filters

I tried multiple approaches. Top three approaches are shown below. Since the end users, this system has a

mix of technical and not technical people I wanted to make the filtering language as simple as possible.

The filters are written in such a way that novice users who don’t have any clue can also use it easily. New

filters are written in a very normal way without jargons.



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Final design

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#4.  AND & OR operations


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Final design

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Below are some of the visual design screens from the system.

  • A list can be created from full customer base or from a specific segment group. 

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We had a 2-week sprint cycle for this project. I actively worked with the Engineers during the development phase.

After every sprint, the Engineers showed me the built flows, and I made a list of gaps such that they can work on

them later. Then, the Product Manager and I sat to prioritise these issues such that the Engineers knew what items

to pick up next. We used Google Sheets to track this progress.

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