Credit Union Geek

Marketing, Strategy, and The Force by Joe Winn

Tag: Facebook (page 1 of 2)

Insights In 160 Characters…Or Less

Full posts are overrated. Ok, that’s not true. They are essential to delve into an issue beyond surface discussions. However, there’s also a time for brevity. Short and sweet, as you could say. I’ve found that much of my best wisdom has originated, spur of the moment, in a Twitter post or reply. If only I were as witty and intelligent in the rest of my life!

There has been a trend lately in terms of topics discussed, both for myself and the industry as a whole. Social Media and Big Data. I’ve written a lot of articles about both, but, let’s be honest. You wouldn’t read them even if they were linked here. However, I might get you to read a series of tweets which spur some new ways of thinking. Ready? Too bad…we’re off!

Social Media

On replying to online criticism/comments:

On producing content your members want to see:

On the difference between good and unique:

On catching attention, in almost any way you can:

On what (actually) makes credit unions different:

On reminding us all that failing is ok, too:

Finally, on being *that guy* in the conversation:

Big Data

On using for “any and all purposes”:

On understanding what you’re looking at:

On realizing nothing really has changed:

On having my A/C replaced:

Did any of those short statements/replies educate, inspire, or convince you of their importance? There’s always more where they came from. Simply follow me on Twitter @JoeCUGeek or comment on the post to start a new conversation!  I tried to share tweets which did not link to long reads, but some do slip through (most of mine go to something to dive deeper).  Also, I realized that searching through 4,000+ tweets is a pain for me, but a victory for you!

Bonus for reading to the end (or just scrolling to the bottom):

The Interview Which Began With A Tweet

Originally published on CUInsight.com

A few weeks ago, I stumbled upon a series of tweets from a credit union member to no one in particular. That I saw it at all amongst the mass of data is odd. But here’s where it gets interesting. The member had an issue with their credit union, Idaho Central Credit Union, and said so in a tweet. They didn’t @ mention the CU or # them, either. So, really, there was no simple way for the credit union to ever know about it. The member was, for all intents and purposes, yelling into an echo chamber.

But the credit union did reply. And thus the origin of this post.

After seeing how the credit union located this member and solved their problem (all through Twitter), I contacted them directly. Unsurprisingly, their Twitter account had a friendly reply, wherein they referred me to the social media/marketing director, Lisa Davis. The following is an interview conducted with her. This credit union, and their team, get social media. I wanted to help them share this strategy with you.

Joe Winn: Good afternoon and thank you for taking the time out for this discussion! As mentioned, I recognized your social media efforts were far beyond the norm when you plucked a member complaint out of thin air (in a sense) for resolution. How did you do that?

Lisa Davis: I work with a couple of systems to grab any mentions of us – monitoring a number of different keywords. We really want to keep tabs on what is being said about us (good and bad) on social platforms, news articles, review sites, etc. We go after negative comments and try our best to turn them around. This is not just great for our members, but is a wonderful way to display how amazing our customer service is to those watching that are potential members.

Winn: I sure was impressed! From their posts, it seemed the member was as well, which is what really matters. What spurred ICCU to develop a social media presence?

Davis: We felt and feel that social media is a great way to connect with members and potential members.

Winn: I agree. How did you inform your members it existed?

Davis: We started off with just a Facebook page and did some fun promotions—contests and whatnot to gain followers. We also had “Like us on Facebook” stamps made up for the tellers to spread the word. Now, we advertise all of our social platforms in the branches on the screens behind the teller line. In addition, we do run Facebook/Instagram ads.

Winn: Engaging the “what’s in it for me” mentality is a good strategy. Of course, I’m sure it wasn’t all roses and massive follower adoption. What missteps (if any) did you encounter as the system grew?

Davis: In the beginning, we weren’t catching as many mentions since people use a variety of different names for us. This is what prompted us to look into monitoring software – which has proven very useful, especially since as we continue to grow, mentions are growing as well.

Winn: So that would be how you caught this member’s complaints to no one in particular. Given a member can ask anything online, is the social media platform effort engaged with all CU departments, or just routed through a specific team?

Davis: I manage all things social, but work with many teams to accomplish our goals. For example, we strive to follow up with anyone who has an issue or a question – whether they request follow up or not. Based on the question or concern, I facilitate these through the appropriate team member and then make sure the person has been contacted and then follow up on our social channels so the public can see that we have addressed it.

Winn: Sharing these resolutions is a smart move. It’s like when a restaurant responds to reviews on Yelp. Always makes me feel like they truly care. How do you feel member support and outreach will grow in this medium? Will it become just another option for members, or will it begin to replace existing platforms (live chat, phone, e-mail, even in-person)?

Davis: I feel that [social media as a member support and outreach medium] will continue to grow. (emphasis mine) As we…grow, we have definitely watched our member interaction through social channels grow. We have some members who use social media as their primary way to connect with us – to inquire about a new product, provide feedback on a recent interaction, or ask a question about their online banking. Social never really shuts down for the day. Although, it is not expected, if I get a question at 10pm on a Saturday night, I’ll answer it. Our members know they can count on us through social to at least get feedback that their question has been passed along to a team member who will get in touch with them shortly after the opening of next business day. I think this makes them feel more connected to us and builds a level of trust and security knowing they have a place to go with a question or concern 24×7. (emphasis mine)

Winn: Well, I’ve definitely gained a level of trust through this discussion. Thank you again for your time and for sharing these insights! I’m certain readers from other credit unions will enjoy learning about your strategies and the passion committed to making it the best it can. This reflects, as you intended, positively on Idaho Central Credit Union.

Follow Idaho Central Credit Union directly through their Facebook, Twitter, and Instagram pages! Visit their site for even more ways to connect.

So, fellow geeks (and honorary geeks)…what did you think of this interview? Want to see more discussions with your peers? Let me know in the comments below!

Image credit: http://freshspace.co/blog/wp-content/uploads/2013/05/Twitter-Help.jpg

Be Your Member’s Favorite Stalk…ahem, Tracker!

Update 8/18/16: During a recent National CU Foundation Twitter chat on financial wellness, I posed a question about how these credit unions are able to locate members who may not realize they need help.  Or not even know help is available…from anywhere.  Coastal FCU (Raleigh, NC, $2.6B) responded with: “A lot of it is data analysis. You look for indicators and warning signs in your member activity.”  They’re using the same concepts of Big Data which I discuss below, but for an amazing purpose: Helping their members who may not even know they need (or can get) help!  To paraphrase the end of this post, it sure sounds like they’re “maximizing the connection to their members” and “delivering a higher standard of service” for all of them!  How do you use data analysis to help your members?

Originally published on CUInsight.com

I know what you did last summer.

It’s funny to think how just a few years back, this was a terrifying proposition. “Oh no, our stalker knows!” Now, your stalker is any given friend who checked your Facebook profile. Or, more true to our topic…Facebook’s algorithms showed me your activities proactively. That hiking trip you took triggered markers that are similar between us. Facebook knew I would enjoy seeing your vacation photos.

This is one direct application of Big Data. It’s a topic so complicated that I could spend an entire year of posts delving into the principles. But I won’t (you’re welcome!). Instead, I’m going to try to offer some examples so you can understand the opportunities it presents.

By keeping a digital eye on everything I post, share, like, and comment upon, Facebook’s “Big Data” engine learns my preferences. Maybe I tend to Like many things one friend shares. That’s an easy conclusion; show me everything from that friend, because I’ll probably enjoy seeing it. What about that friend I haven’t spoken to in years, yet shares photos from Machu Picchu? Facebook knows I was there last year, so it’s likely I’ll be interested in seeing their adventure in the same place. More so, I always seem to share/comment on posts regarding ocean conservation. From what I say, Facebook knows I’m interested in environmental responsibility, so I’m going to see more of what friends say regarding this topic.

These examples are rather pedestrian. See a pattern, follow to result. Yet Big Data gets interesting when it starts drawing conclusions. Facebook can determine your political stance, religious beliefs (intensity or lack thereof), income level, and other character traits with stunning accuracy. It can figure out your emotional state, both short and long-term. This is why you get those anti-depressant/counseling ads when you’re feeling your worst and wedding planning ads after you’ve been in a rewarding relationship. A popular example of this predictive capability was when a department store sent a woman a baby catalog before she even knew she was pregnant.

Big Data isn’t just about having thousands of lines in a spreadsheet. It’s the ability to take all this data and gain valuable insights which can be put towards a better product/service offering. Like your member programs.

Too many credit unions I speak to have little to no tracking, no matter the program. I’m not talking Artificial Intelligence level analysis, just a few numbers to know what’s happening. Are your initiatives successful with the members you had hoped? What percentage of website visits results in a loan application? How do you compare to other institutions in performance metrics? And so on.

I’m a huge fan of data analysis because there is just so much information hidden within even the smallest datasets. Here’s an example from my business, starting with these data points:

  • # of member prospects
  • # unique visitors to website
  • # of sales/loans
  • # of members at credit union

From these four values, I can determine the following (with comparisons to all other credit unions for each):

  • Sales ratio
  • Unique visitors per 1,000 members
  • Prospects per 1,000 members
  • Prospect close rate on a rolling 60-day period (along with average close rate among all credit unions)
  • Sales per 1,000 members
  • And I can generate even more on demand

With access to your basic member information, you can easily determine dozens of behaviors and trends. Take your auto loans. Do members living in a certain ZIP code prefer Toyotas? Or do some ZIP codes have higher used car purchase ratios? You may even find that members with last names shorter than 5 letters, who also have your credit card and a CD, buy vehicles with a 10% higher down payment average than other groups. How can your marketing team take advantage of this new information? Sure, that’s a silly dataset, but it shows how much you can dig into what you already have.

Do all of your services meet the Big Data Test? Take the average member referral program. If you’re like the vast majority of credit unions, it requires a member and friend print out a PDF, fill it out by hand, then fax or bring it into a branch. Test results: Fail.

At the end of the day, embracing the ideas of Big Data helps to maximize the connection with your members, thus, delivering a higher standard of service at the lowest effort and cost. And isn’t that the goal of your credit union?

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