Navigating the Data Universe
The journey to meeting a company's goal is deceptively simple on paper: develop a product, find customers to purchase it, make a profit. If only it were that easy. We all know it's not.
Businesses are facing new forks in the road to profit every day. Customers' tastes change daily, ahead of the speed of business innovation, and these customers are demanding new ways to purchase and interact with products. While the barrage of data about their customers in the past two years might have thrown a wrench into companies' CRM strategies, this data is the answer to finding truthful, fuller customer community patterns—the kind that will act as a guide star for business.
CRM Data Constellations
Humans spot patterns in the stars from their perspective on earth. There are anthropomorphized ones that are familiar, such as the Big and Little Dippers. There are more still that are just as significant, yet have less obvious shape, or that might be of a magnitude that was overlooked before. Big data analytics can serve companies by elucidating which patterns are important community-based information and which are ill informed, inherently misleading assumptions and biases that are made from the perspective of the CRM manager.
By accessing the broader, previously invisible connections around individual and community customer data, CRM managers will be able to better target the needs of loyal customers, figure out which groups of customers to avoid, and better tailor consumers' experience based on constellations of user information. The data universe is not limited to CRM data collected by companies now, though. Available data around social media, location data, and other sources provide a fuller picture of the data landscape. Better management of the universe of data available to CRM managers will lead to increased profit, decreased inefficiency of product offerings, and a happier relationship between customers and companies.
Here are a few ways big data analytics and CRM pair to allow businesses to develop better services and relationships with their customers.
Improving Telecommunications with Big Data
The telecom industry is a big data player because it's one of the instigators of the massive growth of available data. Consider, for instance, previous billing methods versus current methods at mobile service providers. It was impressive when detailed, multipage bills were sent to customers about their text and call usage. Such detail is impossible now, because users perform hundreds of tasks on their smartphones daily—the least of which are phone calls—and there are millions of customers at each telecom provider. Add landline-based telecommunications and CRM databases snowball to gargantuan scales.
Telecommunications companies can use big data analytics on their CRM databases to tease out useful, potentially surprising constellations of data across a number of user communities. Big data could lead to a better ability to keep up with constantly changing privacy regulations, be a tool for paring down offered service packages to increase profits, detect which customers have behavior patterns and profiles that indicate they are most at risk of leaving the service months before they do, and provide services to customers that are more easily manageable by the company.
Telecommunications could also better interact with the social media data created on and through users' networks to develop a fuller understanding of the user, their networks of friends and family, their desires, and the difficulties facing them that might affect their use.
Big Data in Your Shopping Cart
Retail is another industry that produces a mind-boggling amount of data through CRM systems. Everyone's favorite data-centric stat for retail is WalMart's more than 1 million customer transactions that happen every minute. Clearly not every company will have this kind of customer base, but most companies are facing large, data-centric challenges that could be ameliorated by the use of data analytics.
Imagine your favorite department store on a Saturday afternoon. You turn to a table of shoes that are on sale and decide to try a few on. A helpful salesperson approaches you and queries the stock available in the back room for your size and width in two styles—they have one of the two available in your requirements. You walk away due to this oversight in the stockroom. This is one of the most popular styles this year. How could they have not anticipated the demand?
Retailers have moved toward using technologies like the handheld mentioned above to expedite customer service on the floor. These machines help generate even more data on the customer base and their desires. By delving into the CRM data from encounters like these and pulling the important insights through analytics, the store could improve its product mix to include more shoes in the person's size, less shoes of a less popular kind, make recommendations based on shoes with similar attributes, and improve both profits and customer relationships.
By going even further—analyzing the number of hits made to the Web site of shoes that are offered in store, the number of times the shoe was featured on various fashion bloggers' Web sites and Pinterest boards, and finding other categories of items that consumers tend to buy with a particular item—CRM managers can create graphs of influence: who buys what, when, in what quantity, and how we can best get the product sold while reducing purchase of goods that won't turn.
Your Data Is Here to Stay. Use It Wisely.
The bottom line for businesses is that CRM data is here to stay, that it will continue to grow, and that there is a whole universe of data available to broaden analytics even further. Businesses that do not seek out targeted, CRM-based analytic solutions are less like modern astronomers and more like ancient sailors lost at sea, searching for a guide star that would be visible with more information and better tools.
Radhika Subramanian is the CEO at Emcien. She is a seasoned entrepreneur with decades of experience helping organizations utilize the insight buried within their data. Tweet to @RadhikaAtEmcien and join her Big Data Apps LinkedIn group.
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