At the 2017 ARDA World Conference, the Sales and Marketing Forum took on the challenge of reimagining the sales process. Following a brief panel discussion on challenges and opportunities for the industry, approximately 100 industry professionals participated in round table discussions focusing on various sales activities and then reported their ideas back to the larger group. One suggestion that intrigued me was the idea of using big data to better match consumers to the products they’re offered at the sales table.At the 2017 ARDA World Conference, the Sales and Marketing Forum took on the challenge of reimagining the sales process. Following a brief panel discussion on challenges and opportunities for the industry, approximately 100 industry professionals participated in round table discussions focusing on various sales activities and then reported their ideas back to the larger group. One suggestion that intrigued me was the idea of using big data to better match consumers to the products they’re offered at the sales table.
Big data has been one of the hottest business topics over the past few years, but it seems that the joke that began making the rounds in 2013 is still accurate: “Big data is like teenage sex: everyone talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it.”
What is “big data”? This isn’t the dictionary definition, but the term generally refers to the way advances in data storage, such as the “cloud,” combined with innovations in analytics, allow service providers and marketers to gain new insights into consumer preferences and habits. Daniel Green, chief revenue officer at the Levitan Group and a co-founder of Trooval, a company that used predictive analytics products to assist timeshare developers, says, “Big data is a somewhat ambiguous term that gets thrown around without any consistent definition. In the context of this conversation, I define big data as a macro approach to managing the whole business as one organic, living, being. Data, when used correctly, tie the disparate silos of your business together, making a metrics-based approach to smart decision-making possible; by asking the right questions you can confidently predict the outcome of any one action across every department.”
Going BigHow much data does it take to be “big,” and are we there yet? According to Sean Nickerson, co-founder and vice president of marketing at TrackResults Software, a Utah based company that offers business-intelligence solutions for the shared-ownership industry, big data is measured in petabytes, which are the equivalent of 1 million gigabytes. “Big data is the wrong term for what we’re talking about in our industry today,” he says. “We don’t have that as an industry. However, there’s a lot that can be done with smart money”. Some companies suggest targeting the information that we do have, such as what magazines people subscribe to, where they live and what websites they visit.
In the sales process, Green sees great potential for using the data currently available in the ways that the forum participants suggest to better match consumers to the right product—and to reinforce consumer loyalty.
“Many people mistake volume of ownership with product satisfaction,” he says. “If folks are satisfied with your product, they’re most likely loyal customers. But how do you really know? Gut? They’ve never missed a payment or been late? They come to their home timeshare resort each year? They have family that also own? The answer is, we don’t know what makes a customer loyal—not by looking at singular, or small sample sets of data. They didn’t miss a payment? Great, they care about their credit; what does this have to do with their loyalty to your product or their need for more? Do they come each year? Awesome. Maybe that’s all they can really afford.”
“When we make data-less decisions, we make costly mistakes whose consequences aren’t seen for years. That family that doesn’t miss a payment, who just bought more to ‘solve’ a perceived problem? This new sale will kick them over the edge, causing them to default, leading to foreclosure, within three years. Big data, or better yet, big analytics, provides future insight, today.”
Underselling a buyer also has potential disadvantages. “Underselling while overpromising destroys credibility and undermines the success of the developer by creating unhappy, and disloyal, customers. You’ll get a bunch more money out of them over the next few years as they eventually, piece by piece, buy the product they need. Think about that. Because we didn’t sell them the right product first go-around, the new ‘owner’ attends a presentation every vacation they take, is told they don’t own the right product on every vacation they take and is made to feel obliged to upgrade ownership on every vacation.”
At TrackResults, Nickerson is currently using large volumes of data to assist timeshare companies with their sales and marketing efforts. During the sales process, developers are matching prospects with sales representatives based on data points, such as age, interests or level of educations. These matches are based on the documented historical performance of each sales rep when matched with similar prospects. This use of data allows sales reps to be paired with prospects that have this highest probability of closing a sale. “Knowledge is power,” he says. “This approach allows our clients to give their sales rep every possible advantage.”
The same logic applies to the marketing process. “We review real data for marketing across the globe,” Nickerson says, “We’ve found some areas have a higher propensity to respond to traditional marketing.” He cites a specific example from a study that TrackResults performed for AMDETUR. When asked who has the highest close rate for purchasing a timeshare in eastern Mexico; millions of dates points were examined. The answer surprised even him. As it turns out the highest close rate at the time belonged to cohabiting heterosexual couples from Minnesota. While there can be many theories why the data proved that it was the case.
Nickerson says, “Of course, many developers are already doing some of this by targeting ads on Facebook based on demography and user profiles, but they’re just starting to scratch the surface of what’s possible.”
To get started, both Nickerson and Green recommend turning to experts in this area rather than trying to go it alone. “If you don’t know what you don’t know, you’re setting yourself up for disappointment,” Nickerson says. Companies such as TrackResults can assist with both storing the data in a usable format and the analytics needed to gain actionable intelligence.
Green advocates the idea of hiring a data scientist. “If you can’t justify the cost, then you really need to hire a data scientist; they have a wonderful way of finding gold in the seat cushions,” he says. Internal resources are probably not the answer today, he says. “Business analysts can provide a great Band-Aid, but predictive is where the value lays. And you need a professional for that.”
4 Steps to Harnessing Big Data
Develop a Strategic Vision. Determine what data and analytics can be used for. Create strategies to measure success.
Build the Data Pool. Move data from departmental “silos” to collective resources. Capture information from customer interactions, open source data, and purchased sources. Maintain data hygiene to assure the accuracy and usability of the information collected.
Acquire the Skills to Use the Data. Hire a chief data officer, build in-house capabilities, outsource to specialists or, most likely, combine these approaches.
Incorporate Data Insights Into Your Business. This means that the right personnel
to have access to the right data, and that top and mid-level managers must be trained to rely on data-driven insights as part of their decision-making process.