Simplify, clarify, align, and focus on the metric that matters. That was the overall mood of the Direct Marketing Association’s conference held in New York this week.
The DMA promotes reponsible data-driven marketing, and the consistent theme at Integrated Marketing Week was how to handle dizzying quantities of data in an organized and directed way. Instead of an emphasis on the need to aggregate as much data as possible, and automate its use to identify and message countless prospects–as individuals, moreover–in real time, IMW speakers regrouped around the personal touch, carefully edited data, and clear goals. A refreshing approach, although it’s going to be increasingly challenged by the rapidity of data growth and tech evolution.
Let’s take a closer look.
Approaches to Big Data
Scott Ellis of Adworthy outlined a use case in which his company leveraged data to manage growth for a successful Australian IT service start-up, Geeks2U. The outcomes seemed to good, but what struck me was his starting point: “How do we filter out big data?” How do we stop data pouring in and drowning the strategy? With 200,000 customers (a big chunk of market in Australia), Geeks2U had plenty of raw data about users–but that’s the last place Ellis would look for ideas on market expansion. Start, instead, with the business goal; identify the channels to be used to reach the goal; figure out success metrics; and only then look at the relevant data. By filtering the data upstream, you make it, Ellis said, “smart downstream.”
Sounds like the human touch? I heard similar thoughts from Theresa Morrelli of IBM’s Customer Analytics Solutions division. “Don’t try to boil the ocean right away,” she said. “What’s the metric I really care about?” And from Anne Gherini, head of marketing at the ad-driven Internet curation site StumbleUpon: “We get so much data now, you have to run that balance between looking at the data, and stepping back and remembering–these are not numbers, these are people.”
I needed someone to help me understand this balance between the human and the data-driven, and I sat down with Menaka Shroff, head of marketing at BetterWorks.
Qualitative Trumps Automation
Shroff has the singular advantage of many perspectives on the evolving marketing strategy and technology scene. She spent five years as a sales rep, so she’s seen it from the field. She spent over four years as director, then senior director of product marketing at Box, helping it grow from six to 20 million users, and from 40 to 1,000 employees. At BetterWorks, she’s marketing a software solution which lets business goals cascade from management to individual employees, and helps track progress and milestones. What’s more, her Silicon Valley location keeps her in touch with innovators and new solutions.
In conversation, she kept returning to the value of human contact and agility in the face of challenges. Qualitative marketing, she still believes, “never gets substituted by automation.” For example, she thinks getting a single, connected view of the prospect and following it across channels is far from an insurmountable challenge–Salesforce and Marketo, she said, manage that quite effectively. What is often lacking is adaptability in using the information. For example, you may think that goal-setting software will sell to HR heads. You can surface the right personas from the ocean of Salesforce or Marketo data, but when you realize that purchasing is actually a C-level decision, you need to stop and rethink your strategy.
Similarly, when it comes to asset management, it’s important to have a centralized platform for content, and to be able to track revisions and update core assets accordingly. That’s where automation helps (she says Box is a good solution for collaborative asset management). But when it comes to getting the message right–“the nuances of the message, and avoiding jargon”–there’s no substitute for sitting down with reps or agents and explaining the brand message as many times as necessary.
More than that, she thinks it’s important for marketers to actually be physically present for parts of the sales cycle–shadowing sales calls, for example, not least to hear what customers say–in order to ensure an alignment between the brand message and the message in the field. “There’s definitely more convergence today between marketing and sales,” she said. “But what’s important is to have the roles defined and aligned upfront–every quarter, or every two weeks if necessary.” Once you break free of the “Why aren’t you converting the leads?” versus “The leads are no good” conflict, marketing and sales can start to have more strategic conversations.
As for customer data, what’s important is that the business which owns the data defines its location. Shroff is a believer in an open stack approach to marketing technology. BetterWorks takes an à la carte approach–Marketo for email, Salesforce for CRM, Sprout Social for listening–but insists on defining where the central prospect or customer profile is located. She admits that one vendor stacks can work for some companies: “I want freedom in picking the best for what I want to do.” The Silicon Valley influence, she thinks.
Being Smart About Data
Ellis too kept a human eye on the data aggregated around Geeks2U’s customers. Analytics showed web traffic originating in city centers, like the Sydney Central Business District. Geeks2U specializes in home visits to service computers. But nobody–next to nobody–lives in those city centers.
The solution, of course, was that the target audience was commuting, and shopping during the working day for a service they’d consume at home. Buying spots on drive time media would reach that audience, aligned with billboard advertising. The lesson was that looking for patterns in the data in an undirected way, and launching an automated response, made less sense than developing a “simple, replicable, and scaleable” framework for looking at the data. Trusted for in-house service, Geeks2U is re-positioning itself as a general adviser on home technology–IoT installations, for example–and learning how to use data to find the right prospects, at home or on the way to work.
It looks like data-driven marketing still leaves room for interpretation and creativity.
