Are You a Data Hoarder? We’re Betting So.

As an analyst on Forrester's Customer Insight's team, I spend a lot of time counseling clients on best-practice customer data usage strategies. And if there's one thing I've learned, it's that there is no such thing as a 360-degree view of the customer.

Here's the cold, hard truth: you can't possibly expect to know your customer, no matter how much data you have, if all of that data 1) is about her transactions with YOU and you 2) is hoarded away from your partners. And this isn't just about customer data either -- it's about product data, operational data, and even cultural-environmental data. As our customers become more sophisticated and collaborative with each other ("perpetually connected"), so organizations must do the same. That means sharing data, creating collaborative insight, and becoming willing participants in open data marketplaces. 

Now, why should you care? Isn't it kind of risky to share your hard-won data? And isn't the data you have enough to delight your customers today? Sure, it might be. But I'd put money on the fact that it won't be for long, because digital disruptors are out there shaking up the foundations of insight and analytics, customer experience, and process improvement in big ways. Let me give you a couple of examples:

  • Lowes Home Improvement stores realized that they were missing a crucial layer of insight about store performance and customer experiences, because they couldn't see what sales barriers they were creating inadvertently. They created a portal where suppliers could access, analyze, and share information like geographic penetration, product cross-sell data, and POS data. Using that knowledge sharing, they discovered that they had made a critical inventory mistake that negatively affected sales of a specific product; correcting that mistake turned that product's sales around dramatically.
     
  • Pacific Gas & Electric, a California utility company, realized that it had a unique opportunity to get consumers a lot more engaged with their energy usage. But the company's core competency isn't exactly in creating mobile apps or other customer engagement solutions. Instead of hoarding its data and trying to go it alone, PG&E opened access to energy usage data via APIs -- always considering privacy and permission -- to a few authorized third-party developers. The result? Three very cool apps that help users understand and manage their energy use, and show them how to save money by reducing and optimizing their usage.

These companies -- and many more that are profiled in our recent report -- are on their way to achieving Adaptive Intelligence, which we define as:

Real-time, multi-dimensional sharing of data in order to derive contextually appropriate, authoritative knowledge that helps maximize business value.

 

My collaborators -- Eve Maler and James Staten -- and I encourage you to read this seminal new research, and ask yourself these questions:

  1. How much better could I run my business if I could share insights, collaboratively and in real-time, with my best business partners?
  2. What data do I have that might be valuable to my partners and peers, and what is that worth to them -- and me?
  3. What must I do to share my data in a permission-based, well-governed way in the future?

And, as always, we invite you to reach out to us, via a comment here, in our communities, or via the inquiry process. We look forward to hearing your thoughts about AI, and helping each of you achieve this state of organizational intelligence!

Fatemeh Khatibloo will presenting on the data challenges related to the "perpetually connected" and personal identity management at next week's Forrester's Forum For Marketing Leaders EMEA in London (May 21-22).  

Comments

Thank you Fatemeh. I'm

Thank you Fatemeh. I'm familiar with the problem you're describing. Transactional data, marketing data and customer service data is so much more powerful when it's brought together. Outside of those low-hanging fruits, what other helpful but hidden data resides in partner's hands that could improve the customer experience? Probably more than we think. Looking forward to reading more about Adaptive Intelligence.

The challenges of data sharing

Fatemeh,

This is a hobby I agree business should subscribe to. But in my experience many are unable to optimise the richness of the data they hold already - this being the 'who' and the 'what' behavioural data. Adding new layers of external intelligence can just exacerbate the situation. Or as a data planner once put it to me, "we can't make anything out of the lego bricks (data) we have already, so how do we know we will be able to make something when we borrow someone else's lego?"

For me, this type of collaboration is a three stage approach; 1) have an idea of why you are fishing in the first place (several hypothesis to clarify/break down 2) fish in several ponds rather than the one that is presented to you 3) have the talent to turn what you catch in to a much tastier offering than you produced before.

Of this process 2) is the easy bit. The challenge is being insightful/intuitive enough to know what to look for rather than relying on the date to drive it out and the real trick is having the quality of interpretation to convert the new data findings into solutions which are motivating to customers, achievable for the company, brand enlightened and commercially sound.

In my experience, more of stage is where scarce resources are often best applied - rather than fishing for new lego (to crash my two odd analogies together.

Really interesting topic though. Thank you.

Christopher

The challenges of data sharing v2

Fatemeh,

Apologies I hit send before I'd checked V1, so here's a checked V2!

This is a hobby I agree business' should subscribe to. But in my experience many are unable to optimise the richness of the data they hold already - this being the 'who' and the 'what' behavioural data. Adding new layers of external intelligence can just exacerbate the situation. Or as a data planner once put it to me, "we can't make anything out of the Lego bricks (data) we have already, so how do we know we will be able to make something when we borrow someone else's Lego?"
For me, this type of collaboration is a three stage approach; 1) have an idea of why you are fishing in the first place (several hypothesis to clarify/break down) 2) fish in several ponds rather than the one that is presented to you 3) have the talent to turn what you catch in to a much tastier offering than you produced before.

Of this process 2) is the easy bit. The challenge is being insightful/intuitive enough to know what to look for rather than relying on the data to drive it out and the real trick is having the quality of interpretation to convert the new data findings into solutions which are motivating to customers, achievable for the company, brand enlightened and commercially sound.
In my experience, more of stage 3) is where scarce resources are often best applied - rather than fishing for new Lego (to crash my odd analogies together).

Really interesting topic though. Thank you.

Christopher