Marketers Integrate Customer Experience Data in Drive to Grow Revenue

by   |   September 19, 2013 12:36 pm   |   0 Comments

Above, a screenshot from a Scout Analytics application segments customers into up-sell opportunities (green), cross-sell candidates (blue) and retention risk customers (red).

Above, a screenshot from a Scout Analytics application that segments customers into up-sell opportunities (green), cross-sell candidates (blue) and retention risk customers (red).

EDA is in the market intelligence business – it sells data subscriptions to organizations that make, sell, service or finance equipment in industries like agriculture and construction. But prior to the spring of 2012, EDA was missing critical pieces of intelligence about its own customers: Data relating to their usage of its tool.

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Though EDA could access users’ last two logins, it was extremely difficult for it to determine which individuals within a company were using the tool, for example, and what customers were doing once they logged in. Were they using search filters to derive prospect lists? It was hard to know.

EDA didn’t have a holistic view of its customers. It’s a common problem: a 2013 Teradata survey found that of 2,220 marketers queried, just 18 percent have a single view of the customer even though it’s one of their top priorities for future improvement.

“There’s so much more data than we’ve ever had before, and the realization is there’s an opportunity there to understand the customer through the data to improve the customer experience,” says Paige O’Neill, chief marketing officer of iJento, which sells customer intelligence products to marketers.

Achieving 360-degree views of customers is challenging for many reasons. Topping the list: Customers have many interactions with a brand, and the information about those varied interactions is often not stored together. “The data could be sitting in so many different places across the organization,” says O’Neill. “It’s coming in from digital channels, it’s sitting in CRM systems, in marketing automation systems, in customer support systems or in call centers.” All that information needs to be integrated.

Likewise, departments often have different ways of identifying a customer. Companies face the challenge of creating a standardized ID for individuals that can be shared across the business units, says Wilson Raj, global director, customer intelligence at the business analytics firm SAS.

Matt Shanahan

Matt Shanahan

And of course, there’s the bigness of the data. Scout Analytics, which works with subscription businesses and other clients with recurring revenue models, has one customer that achieves 100 million usage events a day. (Completing a transaction, having a chat or listening to a song are all examples of usage events).

“Just to store [the data], assign it to each individual subscription, index it, report on it – it’s a big data problem and they haven’t had the infrastructure to record 100 million events a day and make sense of it,” says Scout’s Matt Shanahan, senior vice president of marketing and strategy.

Correlating Customer Data Drives Business Changes
EDA had that big data problem – it wasn’t storing many of its own usage events. And, accessing usage data it did have was complicated because doing so required specialized IT skills to query and write reports.

EDA finally gained good visibility into what users were doing with its tool when it hired Scout in April 2012. Now the Issaquah, Wash.-based analytics firm collects and stores EDA’s usage data and combines it with data about subscribers like their purchase history and revenue size. Scout then puts the information into a format that enables analysis and presents it in a dashboard for EDA.

EDA was able to use its new insights to gauge the perceived value subscribers were getting from its product. That understanding was key as it transitioned to a value-based pricing model for subscribers in January; it made that move as it rolled out a more robust Web-based tool.

Tim Maguire, director of customer experience at EDA, says the data provided a view into different customer segments that informed the pricing model. “We knew who we could maybe go after a double-digit increase [from] and others we could jeopardize the retention of the account if we pursued any kind of increase,” he says.

Tim Maguire

Tim Maguire

In addition, EDA’s customer experience team doesn’t need to frequently call or email customers it knows already have heavy usage. It also has a better idea of which clients might be receptive to a cross-sell or an upsell presentation and, on the opposite end, which might be at risk of leaving because their usage has declined. EDA can take some kind of action to re-engage those customers, like sending targeted emails rather than the single email blasts it used to send.

“[The emails] will be primarily industry-based because we know, for example, if a customer hasn’t logged in over the last 60 days, but sells John Deere equipment in Texas, we want to send specific messages maybe even with specific images to get them logged in,” Maguire says.

Gaining Differentiated Views of Customer “Touchpoints”
Meanwhile, another company in pursuit of a more holistic view of its customers is Cox Media Group (CMG), a broadcaster, direct marketer and publishing company that operates in more than 20 media markets. It announced in August that it hired iJento to help turn its vast information about customers into actionable insights. IJento, which is based in Portland, Ore., will be pulling together data from sources like CMG’s subscriber information, CRM system, ad server, Web analytics and social media.

CMG “isn’t interested in segmenting customers into generic groups,” Alan Segal, senior director, digital insights at CMG, says in a press release. “We want to understand each individual’s journey, how they interact with us across multiple channels and what we can do to make their experience better.”

IJento’s O’Neill says having a single view of customers will help CMG better optimize content, for instance. “They want to get a picture of, ‘How is Paige interacting with us when she browses our channels on her mobile device versus her tablet versus her PC?’ so they can understand how they should be presenting content,” she says. “I think that’s a common desire for media and broadcast companies across the board.”

CMG could also use its integrated data to see if visitors are interacting with ads on its properties and if so, how they are interacting. O’Neill says, “To be able to see how customers are viewing and consuming different ads and how those preferences play out across different devices is another key objective of [media] companies.”

Mindy Charski (, a contributing editor for Data Informed, is a Dallas-based freelance writer. Follow her on Twitter: @mindycharski.

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