How Big Data and Marketing Analytics Can Help Sales

Posted on by By Glenn Gow

data-analytics-numbersThe recent data explosion has spawned staggering statistics relating to the massive new volume of data being produced. We are collecting information via billions of connected devices including smartphones, PC’s, RFID sensors, gaming devices and even our automobiles. It is not only the volume of data changing the business landscape, however—the velocity and variety of data is also increasing at a breathtaking rate.

Sales teams used to be key sources of information for buyers, but access to an extraordinary variety and volume of information means buyers are much less reliant on salespeople than ever before.

The proliferation and speed of unstructured data via blogs, news websites and social networks is now such that potential buyers passively receive information (or in some cases misinformation) about your products and your competitors’ products well before someone from your sales team ever has the chance to interact with them. To succeed your sales teams need to know what your buyers are hearing and saying— and then tailor your sales interactions to match.

Marketing analytics is the answer
In answer to this challenge, we have also seen impressive new marketing analytics solutions. The data analytics industry is growing between nine and 12% a year, with some sources predicting that the marketing technology industry will exceed 50 billion dollars in the USA within the next two years. The latest generation of marketing solutions offers not just statistical data analysis, but also behavioral data and social media analysis that Marketing and Sales departments can use to discover answers to specific questions.

It is now possible to query large data sets with specialized behavioral analytics software and extract insights on subjects once considered very ethereal or philosophical in nature. For instance, you can study the co-occurrence of multiple buyer behaviors from past purchases in order to determine what causality may exist. Leveraging large data sets of buyer behavior allows you to predict when, if and how buyers will purchase your products and services in the future.

On top of these amazing new behavioral analysis capabilities, the same information that buyers are exposed to through blogs and social media is available for analysis en masse to companies through specialized social monitoring analytics applications. Marketing teams have access to rich insights into who is talking about your products, what they are saying and what and who is influencing them.

Do big data marketing analytics really work?
Try googling the words “big data.” Today’s search yields an impressive 1,740,000,000 results. It is probably not very hyperbolic to say that the subject big data comes with some hype attached, though it is clearly not just hype—marketing analytics works to increase sales.
If boiling down human behavior to binary histories sounds like the stuff that only those in the field of research or complex financial transactions can take advantage of, consider e-commerce. That ubiquitous box on Amazon.com informing you that “customers who bought this item also purchased…” is something we already take for granted. Predictive technology is becoming so sophisticated that according to recent news reports, the e-commerce juggernaut may even begin shipping items we have not yet decided to purchase!
Likewise, in an example revealed by Gartner analyst Doug Laney, Walmart stores increased online sales as much as 15%—that’s billions of dollars— using machine learning, text analysis and synonym mining.

In another case released by IBM, Trident Marketing—a marketing and sales firm behind such names as DirectTV, ADT and Travel Resorts of America—used marketing analytics on large data sets from its order systems, call center, CRM package, external credit bureaus and search engine results. What it gained was business critical insight into “when to call a consumer, which product to pitch and which salesperson is best suited to close the sale. Plus, sophisticated analytic models can also predict which consumers are likely to cancel services within 12 months — a metric that goes straight to the bottom line because the company must compensate its customers for consumer churn.” Simply put, big data marketing analytics yield powerful and profitable results.

How to use big data to help sales
With so much structured and unstructured data available, it can be rather daunting to know where to begin a data listening program. Fortunately, as much as business has changed in response to the data explosion, something that has remained the same is the old maxim ‘Begin with the end in mind.’ Here’s a formula for beginning to use big data marketing technology:

1. Come Together: CMOs should engage the vice president of Sales to select specific, achievable targets on how Marketing can analyze data and contribute to social selling. Try areas of ‘low-hanging fruit’ where the benefits reaped will amplify buy-in from all corners of the office, and select pilot members with the right technical skills and open attitude.

  1. Execute, Measure and Celebrate: Keeping an eye on the specific targets selected, and using the focused insights provided by marketing, sales people can learn how to reach buyers online in social media and offline in the real world with relevant information at each step of the buyer’s journey. Be sure to establish a baseline against which to measure and celebrate results to begin molding your organization into one that values marketing technology.

    3. Rinse, Wash, Repeat: The work does not stop there. With the sales department properly informed by the knowledge of what buyers hear, say and do, marketing can begin analyzing anew to see how the market is responding to the new initiatives, and add specific new targets about which to gather insights and expand the pilot program to gradually include more sales team members.

    By listening to what information buyers have access to, and studying buyer behavior through marketing technology, CMOs and their marketing teams are in a position to help the sales team directly. A sales team armed with insights derived from big data analysis and a good social selling approach will offer buyers the vital information they need to buy from you.

Glenn Gow is CEO of Crimson Marketing.

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