Credit unions have spent the last few years scrambling to establish a presence on social media, but the next mad scramble will be analyzing data garnered from those social media channels.
But that may prove easier said than done.
“With Facebook, you can see where your members are, you can see gender, you can see age—that’s all great stuff,” said Bo McDonald, founder and CEO of Your Marketing Co., a South Carolina-based consultancy that works with credit unions. “Turning that into engagement is key—and then turning that engagement into a relationship with the credit union is the ultimate goal. A lot of people are trying to use Facebook simply as an ad platform to post things about promotions and loans and checking accounts, and they wonder why there’s no engagement.”
Meredith Olmstead, founding partner of Social Stairway, a social media consulting firm that works with credit unions, noted that Facebook remains the 800-pound gorilla in the room when it comes to social analytics.
“They’re the real star—hands down,” she said, adding that while platforms like LinkedIn and Twitter offer their own analytics tools, “they’re usually coming along a little bit behind the analytics that are available on Facebook.”
But credit unions hoping to use social media to get a better understanding of specific members’ wants and needs should take note—while there are a plethora of tools available, Facebook and other platforms don’t offer the ability to drill down to the individual user level, but rather can help develop a composite picture of specific segments of their audience, analyzing age, location, gender, interests and other demographics.
“That becomes very useful from a content perspective when you’re trying to engage with people,” said Olmstead. “What resonates with them? That analytic data about what had the highest member engagement rate. Determining the top five or 10 pieces of content over the last 30, 60 or 90 days can help you use that information to inform what kinds of areas you’re going to explore further.”
“You can’t get down to a granular level, but you can, for example, target anyone who is a fan of your page or in a certain ZIP code, or target someone who is planning a wedding and then send them an ad for a wedding loan or a mortgage or some other product. You can’t see the specific person, but you can pick specific lifestyles, demographics and locations,” added McDonald.
Overwhelmed by internal data
Facebook and other sites may offer plenty of tools to help page administrators dig in to the data, but only a small percentage of credit unions appear to be utilizing them. While there do not appear to be any studies with hard data examining those sorts of usage patterns, every social media analyst CU Journal spoke to was candid about the fact that the movement as a whole has yet to truly dig into social analytics.
“They have no discretionary spend,” observed Karan Bhalla, VP of analytics for EXL Services (formerly IQR), a data analytics consulting firm. “Everything at credit unions has to have a direct ROI, even analytics. With analytics, you have a high chance of success, but nobody’s going to come out and say ‘You’re going to have X return.’ It’s a bit of a leap of faith and a bit of taking a chance, and that’s where they struggle. Banks still have large marketing budgets where they can take a chance and do things, but credit unions don’t always have the luxury of trying things and seeing what works—especially small and mid-size ones.”
One other factor, sources said, is that CUs already have so much internal data to mine—including ACH information, spending patterns and other behaviors—that many already have their plate full just with that data, let alone digging in to social media. Add in that most credit unions offer multiple social platforms, each of which has its own analytical tools, and it can become overwhelming.
“This is not the top priority for many of them,” Bhalla said. “They’re dealing with compliance issues, they have to invest in core upgrades—for a small credit union of $200 million, that’s a six-month project where nothing else happens. I think it is a size thing, largely, but also a lack of resources. Even though it’s a relatively new area, they’re waiting to see others that have done it and had it work.”
But Brian Knollenberg, VP of member insights and strategy at Tukwila, Wash.-based BECU, observed that credit unions as a movement may move more slowly than the for-profit banking sector when it comes to some technologies, in part because CUs choose to dedicate their resources more toward giving back to members rather than boosting the bottom line.
Knollenberg was a panelist at the recent Credit Union Analytics Summit in Seattle, and in a follow-up interview with CU Journal, he called social analytics “the last mile of data,” suggesting that it’s much more important for CUs to understand their own internal data, including the products and services that are most commonly used, the channels members use for interactions with the institution and other “low-hanging fruit.”
All in the same boat
The good news, he added, is that plenty of Fortune 100 companies are in a similar boat to credit unions, in part because “it’s a little harder to get actionable data” out of social media analytics.
“In order to analyze data and make it valuable to you, you need to get it in a format so it can be organized,” he advised, adding that Twitter allows users to simply organize interactions in a downloadable spreadsheet.
“You could get some value out of it by looking for patterns of basic data analysis, but at the enterprise level where you have hundreds of interactions across multiple platforms, it becomes a much bigger challenge to aggregate and analyze the data,” he said, explaining that credit unions will often need dedicated staff for those tasks or outside partnerships. “What makes it most difficult is that most of the time it’s just straight word of mouth and people talking, and that makes it more difficult to pull patterns from.”
One of the biggest challenges CUs face with social analytics is the variety of platforms that require data mining, and Knollenberg said that for credit unions who haven’t yet delved deeply into analytics, some may want to start out by parsing their internal data, “which is much more aggregated because it’s in your own system.”
“In order to find patterns across these wall-garden ecosystems, Facebook and Instagram work well together because they’re owned by the same company, but with Twitter and LinkedIn (owned by Microsoft)…it takes some skill to find and massage the patterns within those ecosystems,” he said. “There are tools to help you do that, but when you have a broad reach and a lot of data, typically you’ll find they’re more expensive than you hope.”
Still, there are some tools out there that can help—at least up to a point.
“Third-party apps like Hootsuite and Buffer can help by combining multiple social platforms and collecting analytics,” suggested McDonald. “A lot of credit unions don’t know how easy those tools really are, and they’re either free or very inexpensive…For smaller credit unions with few resources, that would be really helpful for them.”
Bigger fish to fry?
Clay Yearsley, SVP of analytics at Texas Trust CU and another panelist at the CU Analytics Summit, noted that while there is plenty of data that can be gleaned from social media, TTCU hasn’t yet begun mining that material, opting instead for in-house data such as members’ ACH patterns and spending behaviors.
“We’re not that far along at this point…we understand the social media information is out there, but we aren’t currently [mining] that in any way,” he said. “Our marketing team and omni-channel delivery team have their ears to the ground, so to speak…but as far as trying to systematically gather that information and use it to help the member, we don’t have anything formal in place at this time.”
Yearsley also offered a pretty simple explanation as to why more credit unions haven’t yet delved into social data.
“Most of us in the credit union world are laying the groundwork for becoming more data-driven organizations, so we have other fish to fry,” he said. “We’ve got to get the basics out of the way first in order to move on to something that is more advanced, like using any third-party data—especially social media, since it’s unstructured and a little harder for us to deal with than tables and figures and statistics, which is what we’ve become accustomed to dealing with.”
