As readers of this blog will note, we’ve often proselytized about how the new world of customer intelligence is all about building and maintaining a two-way street between you and your customers – listening to what your customers are telling you (not only in your customer-service interactions, but also in their purchase patterns, responses to communications, and channels used) and then responding in a timely and appropriate manner (with tailored products and pricing, targeted offers, triggered and customized communications, and sales and customer-service reps who truly understand the needs of the person on the other end of the phone – or SMS, or chat, or e-mail). This two-way street is enabled by the tremendous advances in data gathering, data storage, data processing, predictive analytics, and marketing technology (sometimes known, in whole or in part, as “Big Data”), and it results in enormous benefits both to the businesses that implement it as well as the customers who use it. Customers have come to expect this level of personalized interaction and reward businesses who provide it with higher levels of repeat purchases and greater loyalty.
So why are we still reading blogposts like this recent one on the Harvard Business Review Blog Network (http://bit.ly/YdcYsY), decrying that, aside from a very few companies (like Amazon), “most brands still have no unified view of what their customers are saying, doing, or buying on their websites, in retail, and across social media?” Why are most companies, in fact, “still embracing the ‘spray and pray’ tactics commonly used during the height of traditional advertising?” Part of the answer to this question is that most companies still maintain data in siloes, so that it is practically impossible to get a holistic, 360-degree customer profile. Another part is not technical, but cultural: most companies still have not embraced this new way of looking at customers and responding to customer needs and expressed interests. Still another reason is that many companies suffer from “analysis paralysis,” caught like deer in the headlights as they struggle to make sense of all the customer data points deluging them on a daily basis.
Our own point of view is that, as we’ve said before, companies need to take a deep, cleansing breath and relax: it’s not possible to “boil the ocean” and create an end-state “big data” solution all at once. In fact, most companies who try this approach fail miserably. A recent Wall Street Journal article entitled “Big Data, Big Blunders” (http://on.wsj.com/ZfJ6vs) notes that 44% of IT professionals had worked on big-data initiatives that were shelved with nothing to show for all the time and money poured into them, and that too many companies “start out with expensive and high-risk big-data initiatives,” with “big-bang implementations … rarely a path to success.” Our mantra here is “thing big but start small” – big data, big results, and a big vision for what you’d like to accomplish, but small initial goals that demonstrate a proof-of-concept, build initial successes with real results, and set the stage for larger follow-on projects that will have senior buy-in because success has already been demonstrated on a smaller scale with the same approach. Starting with one pain-point (abandoned shopping carts, e.g.) and then creating a customer-data-driven solution aimed at addressing that pain-point (sending a targeted follow-up e-mail with a link back to the abandoned cart within 24 hours of abandonment, e.g.), and measuring the results and demonstrating success, will pay huge dividends in getting a larger project off the ground and will really start building that two-way street between you and your customers.
Now, is anyone out there STILL not listening?
