The Trouble With CRM Data

The ability to collect massive amounts of data represented a huge leap forward in customer service and communication when customer relationship management first hit the market as a marketing, sales and data management tool.

However, CRMs weren’t a holy grail. Data management is one thing. Using data to understand what customers really need (not just what you think they do) and how to engage them is another thing entirely.

CRMs were not built to be nimble. Times change, customer expectations change, and the technology needs to change with it.

Currently, predictive analytics and artificial intelligence promise the potential to revolutionize CRMs in truly meaningful ways, but rather than be hyperbolic about that potential, it’s important to be pragmatic — and that’s not the same as being negative.

Sure, applying artificial intelligence to CRMs can make personalization more efficient and effective, but it will truly work only if the solution’s most inherent characteristic is recognition that customer needs have been driving the AI revolution.

In their present state, CRMs haven’t excelled at the uncanny ability to shine a light on information that should be prioritized (based on an organization’s top line goals), versus that which may not be relevant in specific applications. They should.

Moreover, I’d go as far as to say that CRMs essentially are broken, due to several misunderstandings or misapplications of fundamental principles that apply to marketing, sales, customer service relationships — and the data management itself.

1. Siloed data is STILL an issue. The truth of the matter is that CRMs are greedy when it comes to collecting data, but not when it comes to sharing it. This is not a new problem, and yet it persists almost universally across all industries — and not just in organizational functions, like sales.

Siloed data creates walls that prevent anyone from truly seeing a complete image of processes, opportunities for efficiency, and getting an idea of the customer experience from start to finish.

It’s almost incomprehensible to even understand the true value of complete data sets since the data that generally is encountered almost always is found in its fractured form. It’s impossible to optimize a sales funnel, for example, when you don’t really know where or why prospects fall off the path to conversion.

2. More content is NOT better. CRMs have put forth the notion that generating more content is not only beneficial, but also imperative for any organization. This is not true. Creating content for the sake of creating content has been the status quo for so long that most people accept this as something that needs to be done, without asking deeper questions.

In actuality, creating content and creating useful content are two fundamentally different actions. People want higher-quality content because they want to learn how to solve persistent problems that impede progress. Generic messages don’t do that.

After years of being conned by clickbait and fluff that offers no value at all, individuals have become more discerning about how and where they choose to consume content. People have become more tolerant of longer-form content pieces — so long as they provide substance. The yearning is for actual insights or for practical, useful data.

3. Not everyone uses technology the same way. It’s easy to make assumptions about how data might be used, but the reality is that there potentially could be an infinite number of uses or needs for data that CRMs never could have predicted.

The possibilities of technology are limitless, but on a case-by-case basis, the actual needs often are very specific. The assumption that everyone has the same technological literacy to be able to use a CRM for a specific need overlooks the huge segment of the market that does not meet this threshold.

In order to truly understand what data is useful for the creation of personalized and useful content, CRMs have to have a better method for incorporating customer feedback and understanding their own processes.

Understanding how processes unfold, and seeing the connection between all of the operational elements and the corresponding data, is the only way to reassure users that they have implemented the technology in the way that they need to in order to meet their goals.

4. Listening, not talking, is the most important step in understanding data needs. “Successful people ask a lot more questions during sales calls than do their less successful colleagues,” said Neil Rackham, adding, “these less successful people tend to do most of the talking.”

You could say that successful people have been implementing and using personalization for a lot longer than it has been a buzzword. It’s not hard to understand why. Personalization is one of the best, if not the best methods of persuasion.

By asking questions, effective salespeople can position themselves and their products in the best way possible. This means that the truly beneficial exercise in customer communication is listening to your audience; this allows you to have a dialogue with them, as opposed to simply speaking at them because you think you know what they want and need.

Without a doubt, this can be a truly challenging exercise. Nobody wants to spend the time listening to another person’s challenges or goals, especially when most people already are struggling and stressing over their own. However, the ability to listen will help with the creation of substantive content that provides value to the target audience, thus increasing effectiveness.

When innovative technologies such as AI are applied to CRMs and their data sets, the potential for personalization in ways that lead to effective dialogues with current and prospective clients truly can be amazing.

Our team at Wrench.AI aren’t the only ones showing what’s possible. Companies like mParticle, RichRelevance, Crimson Hexagon and Tractica also have been assisting their customers to make better, data-based decisions.

By approaching AI integration through a lens that specifically addresses the end users’ needs and challenges, it is possible to overcome the barriers to using CRMs effectively.

The key to doing this well lies in the ability to develop a listening mechanism that genuinely hears what customers want and need.

CRMs must begin to look at holistic customer experiences with complete data sets, and be willing to incorporate better feedback mechanisms to meet customer needs. Simply stated, CRMs need to pay attention to their customers in order to remain effective.