Demystifying Data & Analytics for Marketers

As an executive and consultant, my observation is that a vast majority of the industry players have not been able to demystify their data challenge and match it with appropriate analytics to derive better results for their businesses. According to me, that is the key to successful marketing in a digital age.

Marketers today are awash in a sea of data, especially those who engage customers through digital media or are attempting to do so. No matter what your market data maturity level is, the best way to approach the data challenge is to ask the following three question (regularly & iteratively):

1. What Data do I have? (The "What"?)
2. If the Data I have isn't sufficient, Where can I get more? (The "Where"?)
3. What can I determine from the Data? (stepping into matching appropriate Analytics for the Data) (The appropriate "Match")

Exploring each of the simple questions above, as they have certain hidden agenda that you need to be aware of:

1. The "What"?: Best approach, is to list the financial and customer response data that is available to you per marketing vehicle/channel and track each data stream back to the source. The reason this is important is because "the best data is often closest to the point of sale". More such data points the more robust your analytical results will be!

2. The "Where"?: Identify data gaps and determine where the data is collected or can be collected. If you do not have direct access to sales transactions, identify the point of purchase and the owner of the data. Incentives go a long way to encourage data sharing in such cases. In still other cases, purchase the data from third parties such as J.D. Power.

3. The appropriate "Match": There is no "silver bullet" to Analytics approach, data dictates the analytical approach and different analytics provide different information regarding the outcomes of marketing events and their optimization. But, when properly utilized, all of them produce viable answers for marketers.

There are three broad categories of analytic approaches: behavior analytics, attitudinal analytics and business case analytics.

Behavior Analytics: It is driven by models (in turn, driven by algorithms). These predict how customers will respond to stimulus such as a promotion, price change etc. In other words, these models manipulate data around a series of variables and produce a simple and often highly accurate prediction of behavior.

Attitudinal Analytics: Not all data you may have is quantitative and a model or algorithm might not be suitable for such qualitative scenarios such as brand awareness, purchase intent etc. Attitudinal Analytics measure opinions and perceptions to forecast qualitative metrics. The most common and legacy attitudinal analytics is the "purchase funnel", to put things to perspective.

When you combine Attitudinal Analytics with Behavior Analytics you discover the levers you could use to invest decisively on your marketing vehicles/channels as now you have combined predictability with both qualitative & quantitative data. Simple!

Business Case Analytics: These are initial "reality check" metrics and produce interesting observations in the form of upper and lower boundaries that can be constantly used to check investment decisions to "keep it real". The most common and legacy Business Case Analytics is "Breakeven Analysis", to put things to perspective.

When you combine all three of the above on your marketing dashboard, you can: qualify, predict & invest with confidence. However, the catch here is (as mentioned earlier) that this needs to be performed regularly, iteratively and in an ever evolving process.

I hope this helps to demystify data and analytics for marketers and for others interested in this topic. Your questions and comments are welcome!

Disclaimer: The article above is purely the author’s point of view and has nothing to do with the author’s association with NTT DATA Americas or other positions held by the author.

About the Author: Nabeel Siddiqui is Director, Digital Services of NTT DATA Americas, he collaborates with global business leaders in leveraging data, analytics & cutting-edge technology to devise business/IT strategies for the future.