The Cuery Cost-Benefit
Price is an enormous decision-making component for most credit unions. Especially among small and mid-sized organizations, there is a real need for the decision-making team to feel they are doing right by their members and acting fiduciarily responsible. Through years of R&D, Aux has found the price tag of a robust data analytics solution to be the biggest problem for credit unions. Most offerings are just plain too expensive, and this is exactly why Cuery was created.
“It is super affordable and it’s competitive,” says Valla. “Before we engaged you guys, we were looking at other data analytics companies. They were quoting us six figures and telling us there would be quite a bit of work on our end. And the way Cuery prices the different data source connections make a big difference. Cuery costs less but we get way more than with other guys.”
Here’s a breakdown of what Cuery offers from a competitive price point, from Valla’s perspective:
- We have access to a variety of professional services, from road-mapping to data scientists.
- We reap the benefits of Cuery working directly with TIBCO and other top players.
- With other data analytics offerings, you get a tool, but you’ll need to know SQL to do your data mining. Not with Cuery.
- Having Cuery removes the requirement for skill and knowledge, as well as potentially needing a dedicated FTE to support the product.
- Cuery is entirely cloud-based (meaning we can access it from anywhere, not just a specific computer or server).
- Cuery is constantly making improvements and doesn’t keep us in the dark.
“So yes, I think it’s reasonably priced. I think it’s competitive in the market space and costs a lot less than some of those huge players out there” [which we won’t name]. To add insult to injury, Valla laments about the outrageous barrier to entry in even getting a data analytics provider to talk to small credit union. “I know they won’t even talk to my credit union – we’d need to be a $1B+.”
What Happens if Your Credit Union Stands on the Sidelines?
Valla is swift with his answer to this question: “I think they’re going to continue to be left behind. They’re not going to continue to be relevant.”
Up until this point, this case study has focused on what happens when you implement a data analytics solution. But what happens when you don’t? Aux has found that many credit unions are pushing the project into the next year, and then the next – hoping when the pandemic “settles down,” they can then tackle implementing data analytics.
But there are two major problems with waiting.
1. Continuing to make decisions that are not backed by data
“You can’t keep making decisions based on your gut instead of data,” says Valla. When COVID-19 hit, many credit unions we knew were going to focus on a new branch, mobile conversions, etc., but avoid data. You have to do the data part to support all your strategic initiatives going forward. “By not having data to back up your business decisions, it puts you at a severe disadvantage over big banks, FinTechs and the Amazons of the world.”
2. Increasing member friction and while competitors decrease it
The problem is that with each passing month – day, even – you lose members to competitors who are using a data solution. “The longer you wait, you’re just going to be that much further behind the eight ball in obtaining a solution and being able to use it. Implementing this type of product is not a quick journey. However, you’ll have a return on investment by being able to use this data to create member journeys and campaigns, and you’re getting revenue and growth back.”