How do you define success for data-driven marketing programs?

I often have been wondering off-late how does one define success for data-driven marketing programs - the reason being tons of hours are spent in understanding data, organizing data, cleansing the data make it ready for analysis and then time taken for building insights by analysts, getting organization-wide buy-in into the insights and developing a roll-out plan, measuring them etc.

The opportunity I see with all this, is a need to clearly define how is a company benefitting with all of this is increasingly becoming critical. No amount of insights & discovery is worth its weight in gold till it becomes actionable and value is returned in dollars for them. Also, another important question is how do such programs get more investments to provide more value year after year? I also don't see this being driven from one corner or department while participation from senior management teams and other departments is critical for its success, adoption and growing investments.

Interestingly as I got thinking about it, I got something from my archives which had an interesting reference to how to define success by Pat LaPointe.

He has got a lovely definition of defining success. Here's the forumula according to him which may be worth looking at:

MNPV Formula for Success

It is a simple summation of all experiences of transforming insights into action and the value it created divided by the number of resources consumed to get this value and this is raised to the power of perception!

From my experience, I agree with him that the hard part is transforming the insights into action in any company. Also, perception of quality plays a critical role as enterprise-wide buy-in is critical for such programs as they need collaboration from other departments like sales, customer service, IT, channels etc. So, continued success of such programs must be exponentially raised to the perception and alignment of metrics & hence the value each of them get from such initiatives.

Would love to hear any other method of measuring sucess of data-driven marketing programs.

Building a personal data vault - so customer-control their data

I was reading an interesting article by Doc Searls on the data bubble where he makes interesting observations on how customers leave a lot of data and information across digital platforms and various devices that they carry, which is being exploited by business today and the need for customers to control the data rather than business controlling the data.  Quoting him:

Their understanding of our identity is not the same as our understanding of our identity. What they have are a bunch of derived assumptions that may or may not be correct; and even if they are, they are not ours.

I completely agree with him. For example, in many of the social network sites that I am member of, I may not necessarily want the data that I have left behind to be available to social media companies like facebook and twitter or make them available to crawlers or made public to everybody who I know in that list without my permission. Also, the invasion of privacy  of information by Location based service providers like foursquare, Loopt etc. is quite dramatic too. For example, I had commented on an airline service that I was unhappy about and some service issues I had faced and immediately I was besieged with a lot of travel offers thro' Google adsense, emails from other businesses etc. Not to mention, my mobile phone data(GPRS) is also open and I end getting junk messages that I would like to get rid of.  My page was covered with ads and I didn't want them anyway.  

In fact, I believe, there is a crying need to build a personal data vault service - a kind of a brokerage house that owns this information and drives memberships & permissions with individual customers. The customer controls the information that she/he gives permission to part with to the service provider. May be there is a revenue share that certain customers may expect in return of use of that information. 

Kaliya makes some interesting points on how to build a personal data ecosystem and what does it take to build one. She has a a vision document where she outlines core aspects of the emerging interoperable, open standards based ecosystem of personal data services – rooted in the core functionality of a Personal Data Store – the vault/locker/services/broker where all an individuals data is collected and stored and managed.



Information & relationships between people must be protected and to make information work harder & effectively, there is a need to give this control to the customer. 


How will search move to discovery for the empowered customer?

In the recent past, i had written saying that we will move in the near future from "search" engines to "do" engines. Looks like Eric Schimdt recently has been talking about serendipity engines as the future. 

Forrester writes about this.

As you look into the future, the distinction between “search” and “discovery” gets muddy.  While it sounds like science fiction to suggest that technology can help search for things you don’t even yet know you want, the opportunities to improve human discovery are very real.  Combining a person’s context—where they are, who they’re with—with their past opinions and actions and the opinions and actions of others can create tremendous value and relevance.

Imagine you’re someone who has positively rated Mexican restaurants in the past.  As you drive through town around lunchtime, your device alerts you to a well-rated Mexican restaurant that is nearby and likely to suit your tastes.  This information may not be welcome at 8 a.m. or 2 p.m., nor would it be welcome to someone who hasn’t expressed an affinity for Mexican food.  It is the combination of social media, individual preferences and context that creates the opportunity for proactive discovery rather than reactive search.

This isn’t about opening your Yelp application on your smartphone and seeing the same search results as everyone else; it’s about having hardware and software that intuits and presents the things you really care about.  There are already examples of simple "Serendipity Engines" available, such as Netflix's rating system—the more movies you rate, the better the recommendations you'll receive.

What is exciting about this future is the continued progress toward empowering consumers. 

How will this evolve over the next few years will be interesting to track. Service & solution providers will need to build and integrate their development around these trends.