Big Data Accelerates the CRM Race
Big Data has a tendency to add dimension and scale to its application, creating a race for relevant information and the sensitivity to apply it effectively. This is certainly true when applying Big Data to today’s already powerful CRM solutions. By layering the where, when, how, and with whom from disparate sources on top of a single brand’s myopic relationship, Big Data is able to unlock the why of an individual’s purchase and use behavior.
For this article, CRM is the relationship database and rules engine that captures information about a customer and their behavior and turns it into a customized messaging and engagement treatments to drive purchase, loyalty, and operational efficiency.
How does Big Data add depth and breadth to CRM’s current behavioral inputs? The below table illustrates four sources of customer data: internal, 3rd party purchase, industry consortiums, and aggressive capture. Big Data’s rapid rise in capability and application (especially in the retail industry) drastically increases the potential to access and apply diverse streams of customer specific data to deepen the dimensional view of his and her daily behavior.
A big factor on how Big Data impacts a company’s CRM is how mature that company is in the capture and application of data. In this capacity, many companies are still working to unlock all the opportunities CRM provides in their internal world. They might tailor their outreach strategy, focusing on warmer leads as defined by a lead score calculated by customer engagement behavior like web visits, calls, and time in current phase. But the marketplace is shifting quickly, and this group will soon be considered laggards to more aggressive CRM practitioners.
In this capacity, many companies are still working to unlock all the opportunities CRM provides in their internal world
At the middle stage, companies have robust CRM programs that augment their already well managed internal data with third party data sources like Axiom or Merkle and link it with marketing and call automation platforms. Imagine an inbound call responding to a direct TV advertisement. Within 2 seconds, the caller’s phone number is matched with a database containing 250 million US population records to feed available demographic and behavioral caller data and calculate a lead model score. With this score, companies can make decisions on the expected value of the call and potentially the type of agent that has the best opportunity for successful outcome.
Loyalty consortiums like MCX and Plenti make the space even more interesting, bringing potentially competitive retail brands with superior market position into partnerships that include access to elements of each other’s data. MCX is particularly interesting joining retail juggernauts like Target, Walmart, Sears, Gap, Best Buy, CVS, Kohls, Mobile, and Chili’s potentially account for 60 percent of a person’s total disposable and household spend down to the SKU level.
In this stage companies apply data about a customer’s entire behavior to unlock the competitive advantage this intimacy creates. Let’s say Target knows from your purchases that you suffer from indigestion but have a weakness for spicy food. Further, they know that you spent $65 at a Chili’s in the same shopping center as your regular Target store just 5 minutes ago. Target anticipates noncommunicated need, sending you an offer for antacids and a reminder their store is open.
In a third and most advanced stage, market leaders like Amazon, Google, and Facebook have applied their mastery of CRM at massive scale and begun to blur the lines of traditional and more aggressive data capture and application. These companies apply their superior product design and market position to acquire additional customer behavioral data and extend their edge over the competition. Amazon’s passive listening and ordering device Echo, and Google’s Nest are examples of data-based Trojan horses masquerading as a consumer product. At the same time, Google and Facebook silently apply web page behavioral tracking built into the standard link and search functions most pages use to connect FB & G+ users to their site.
Advanced companies aggregate non related metadata like app usage, browsing behaviors, geo-location, financial and credit scores to define common threads that can be monetized. They may realize that you have exceeded your average monthly spend and decide not to offer a dining discount, retaining margin for a full price purchase come payday. Or a car company may see the other cars in your search to determine the right product and price to seal the deal. Or Google might realize there are more than 10 people in your house on Super bowl Sunday, making a good time to offer pizza delivery.
Three challenges emerge for these fast track companies who are aggressively aggregating big data sources to apply profitable customer insights:
1. Race for upside: even advanced users of Big Data and CRM are only scratching the surface of the potential profitability and loyalty rewards it can provide. Many parings of information and business outcomes remain to be discovered to unlock the full potential.
2. Data Access vs Quality: More is not necessarily. Don’t get fooled into capturing all available data without vetting its legality, quality, application and impact on the larger customer focused search.
3. Sensitivity = Maturity: Even advanced companies like Target can fall quickly if they do not exert significant restraint in applying the intimate customer knowledge gathered without coming across too creepy.
Big Data promises to expand CRM in new ways, accelerating the capture and application of dimensional customer understanding to better engage them in a meaningful exchange of value. Successful companies need to continue to capture relevant data and develop internal sensitivity in its application. In this manner they will turn expanded customer intimacy into expanded profits.