Collecting Consumer Data – Email, Zipcode, Area Code: Geo Targeting

Collecting data through various sources like Website, Call center or even Online Banners can provide a lot of information about your consumers. Some of the examples are:

Email Address: If a marketing group is able to get a list of clean email addresses, then a relationship marketing program can be initiated which would help create a long term relation with the consumers. Sending out a series of emails based on consumers needs, can help build a loyal group of consumers

Zipcode: Knowing the Zipcodes of a loyal group of consumers can help understand which Geographical areas have higher quality of leads, and then the marketing can be Geo targeted. With the current ability of Ad servers like DoubleClick and Atlas it is possible to geo target online display advertising.

Similar to Zipcode, Area code can provide a density map of loyal consumers and target the consumers to help increase the loyalty and sales of products.

Having more and more information or data about your consumers helps better understand them and thus get your marketing dollars to work.

In the online world, it is much easier to collect this data through various ways – Online banners, Website, Microsite.

Cookie Window, what is it, what is the optimal length?

A lot of times we come across the term – “Cookie Window” or media folks talking – “There is a 30 day cookie window on this campaign”. What does that mean? This means that consumers who clicked on a digital banner or a search result have 30 days to return to your site and take the action that is being tracked. If the consumer had clicked on the ad, it will be shown in post-click activity and if the consumer had not clicked on the ad, it will be tracked as post-impression activity.
The optimal length of the window should be chosen based on each individual campaign or business, it should be tested and then the correct decision should be made. Typically, a click to conversion or action lag report is available from the ad server like DART or Atlas which shows the time tag between the click and the conversion or action. This is very important for DR (direct response) businesses which are trying to either sell something on their website or have a clearly defined action as then they can adjust the cookie window based on that.


As shown from the chart above, this is a clear increase in the number of actions up to day 10 and then there is a decline through day 15 and after that there are minimal actions. Thus, looking at this chart a cookie window of 15 is the optimal length for this business.

Different systems used to measure same metrics

Many times there is more than one system used to track the same metrics. Many companies use their legacy internal systems to track revenue, margin, visits to their site, which they do not want to give up and also use the new systems like DART, Atlas to track the same metrics.

There will never be two systems which will track exactly the same. There will always be a discrepancy among the two, but the two big things are to identify what the discrepancy is and why does it exist.

Once identified the systems should track in the same direction - i.e. if one shows 20% increase in revenue the other should indicate the same.

In my experience, I think the best way to identify these issues is to map the data flows for both the systems. Once the data flow is mapped, then identity how much difference exists at each step. Also, it is possible that one system must have a longer cookie window than the other - this is a very common issue I have seen in the Online Marketing arena. So, these things could impact a lot.

One more thing I have noticed is that - sometimes systems are set to track a different level. For example: System A could be tracking at creative level and System B could be tracking at placement level. System A could be capturing only certain transactions (example - only certain product categories) but System B could be tracking everything. System A could be tracking only post-click data but System B could be tracking both post-click and post-impression.

One of the common example is trying to match Google Analytics Site data to DART Spotlight tag data. Yes, both of them are same company now but they track differently and never track the same. Some of the variables could be: session time, tags not firing correctly, tags not firing every time etc etc.

It can be a tedious process to identify the differences but once identified the reporting/measurement process becomes so much easy....

Creative Optimizer

If we think about large advertisers - advertising over a billion impressions per month, optimization would be very hard or next to impossible. Possibly, there would be over 1,000 live placements and if there is more than 1 creative...GOOD LUCK with that.

But thanks to DART's DoubleClick Creative Optimizer you can set the the metric you want to optimize on - Click-through rate, conversion rate, revenue etc. What the optimizer does is that it dynamically moves the impressions to the creative which is delivering higher click-through rate, conversion rate or revenue...and the great thing about it is that it works at placement level. So, if on one particular placement creative A is performing better - it will get more impressions and if on another placement creative B is performing better - it will get higher impressions. One more good thing about this is that you can set a minimal threshold, example serve a minimum of 10% of total impression for each creative.

However, there are some drawbacks with every good system, one of the biggest that I have noticed is that you cannot start with a set creative split. It always starts with an even split. So, if you have 2 creatives it starts with a 50/50 split.

But hey, optimizing at creative and placement level and that too AUTOMATED, I will take it any day.

Diagnostic and Success Metrics

It took me a while to figure out what is the difference in these two metrics and one day I was explained in a very nice way, which was embedded in my mind.

Success Metric - A metric which the CEO or CMO would care about. Example: Total new clients or revenue
Diagnostic Metrics - A metric which is used to explain or diagnose the success metric if it over achieved or under achieved. Example: Click-through rate, Interaction rate, Landing page visits

I feel it is very important to put them in the measurement plan and also realize if it is feasible to calculate them. The reason I talk about feasibility is that many time due to technological limitations, it is not possible to get all the data required to calculate the metrics.

For example our friends at Google do not accept third party vendors (example: DART) to serve display ads (banner) and thus it is hard to get the number of impressions and clicks or any other post-impression, post-click activity for the banners served through the Google ad network. Yes, I do know that Google just bought DART - and trust me until this day, they do not accept third party tags.

I have been in various situation where earlier it seems feasible to get the data but when the campaign really launches, it becomes hard or impossible to get the data. OR sometimes the correct tags are not put in place which enable to get the data in the correct form.

Measurement Plan

Writing up a Measurement Plan is very important especially for the skeptics. As I have learnt over the years it helps explain the "WHY MEASURE" and the "HOW TO MEASURE" of measurement process for a campaign.

This document is often skipped and this causes problem like the various parties involved in the campaign launch are not on the same page. One example is: The agency and the client being on the different page in terms of campaign objectives, KPIs etc

This document ensures that all the stakeholders of the campaign (agency, brand manager, product manager, marketing team, advertising team) understand that campaign objectives, consumer flow, KPIs, reporting needs, dashboard structure and the reporting frequencies.

What constitutes the plan:

1. Campaign Overview
2. Consumer Flow
3. Tracking mechanisms like DART tags, Webtrends tags, Google Analytics, Omniture Tags, Hitbox tags, email vendor tracking etc
4. Diagnostic Metrics - example: CTR, Interaction Rate, Email open rate, Email click rate, Phone answer rate
5. Success Metrics - example: ROAS, ROI, Conversion Rate
6. Dashboard - showing the key metrics help to understand the performance of the campaign. Data representation is an very important part the process. I will be providing some illustrations soon.
7. Reporting Frequencies

Happy Measuring....