Customer World

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:

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.

Managing data across the enterprise- How semantic web is changing the game

Most often enterprises struggle with siloed data. It's no surprise that integration of data across enterprise is a nightmare. PWC technology report provides some interesting perspective on how semantic web can make it real and ensure it can be done easier than ever before.

Here are some interesting facts contained in the report:

How is semantic web a game changer for data integration?

The disparate data feed into a mashup—a Web application with highly configurable data display capabilities—that updates each time you add a new store site or remove an old one. Other data in the mashup arerefreshed whenever the original sources are updated. By combining various data, regardless of their formator source, you have a wide range of possibilities forgreater insight and context.

The challenges with traditional data integration vs semantic web:

Generally enterprises don't make the best use of their data.

Given the disparate systems and multitude of vintage of technologies( old and new), it is always very difficult for business managers to use multiple source of data for decisions.

 

Getting internal and external to handshake with each other can help trigger power decisioning within organizations

 

.....empower your business users...

with exploration tools that they could use with existing internal data and with external data of their choosing. These tools would let them find the best business cases and make immediate use of the Linked Data technologies at a low cost to IT, since most of these tools are reasonably priced.

Read more

Innovating GE way - Go back to School

Business Week reports:

It's a first, however, for General Electric's health-care unit, which sells $15 billion a year worth of clunky X-ray machines, CAT-scan machines, and ultrasound testing equipment. The health-care division has long been a technology innovator. But it has historically tried to differentiate its products by getting better and faster readings from its instruments—"feeds and speeds" as Lou Lenzi, the general manager of global design at GE Healthcare, puts it. So turning to art school students for ideas is a significant departure.

GE wants to make medical tests easier on both the patients and the operators of the equipment, which means focusing on the human side of the equation, from ergonomics to emotions. How, for instance, could a traditionally monstrous CAT scan machine be designed to seem less ominous to patients already distressed by their medical condition? How could a machine be easier for the technician to use?

"We're looking beyond the hardware. We're looking at the patient's journey."( says Lawrence Murphy, the health-care unit's chief designer (My emphasis)).

Improved Experience

There were other forces at work, too. One of GE Chief Executive Officer Jeffrey Immelt's initiatives has been to call on employees to "Go Big" by targeting large markets and ideas that might pay off in outsized ways. With that in mind, the health-care designers asked the Art Center students to look at how the company's services might be delivered in developing nations 20 years from now.

Making search customer-centric

Alex Iskold has a great post on Read/Write web on how search needs to get a lot more customer-focussed. The key take-out for me from the post is :

• The 'simplicity of thinking' one needs to have when developing products or services.
• It's about analysing 'customer interactions' and customer behaviour' first and then applying them to products or technologies.
• It's the easy usability of the product or service that will determine acceptance and adoption.

Alex writes:

What is perfect search?

It is interesting to ask: What do we expect when we enter a term into a search box? Ideally, we'd like to get the perfect answer right away. Often, we have an idea what that perfect answer should be, and when computer does not get it for us we are disappointed. But are we being reasonable? Can we expect the "perfect" answer all the time?

Consider for example, our interactions with an Information clerk at the mall. When we ask for a location of a store, she may or may not give us the "perfect" answer. She might not know where this store is, she might not understand us or we may not understand what she said. So for many reasons we may not get the "perfect" answer right away.

What is qualitatively different between our experience with the Information clerk vs. a search engine is that with the clerk we have a dialog. When she does not understand what we asked, she has a chance, to say Excuse me, what do you mean?. Google does not do that, it just gives us the results. If we do not like the answer we have to start from scratch.

The problem is that human interactions are fundamentally iterative, while our interactions with computers are mostly stateless. Perhaps we could get to the perfect search results if we could have a dialog with the computer? Clustering technologies, particularly the one offered by Clusty, give computer a chance to clarify: Excuse me, when you searched for Alex Iskold, did you mean to look for Read/Write Web or AdaptiveBlue or perhaps you where looking for static analysis tools that Alex worked on while at IBM?.