Time Stamp: 7:39 InsightSquared captures sales analytics incoming from both managers and customers, which enables consultants and supervisors to use their experience more efficiently. Rather than spending so many hours finding and compiling information, these high-ticket employees can be much more productive and insightful.
As far as technology goes, one of the biggest buzzwords these days is artificial intelligence. It seems that everyone is using it to varying degrees, and one area where it works wonders is data collection and management.
Unfortunately, although AI is excellent at condensing vast amounts of information, companies are still struggling to deploy it efficiently. In this episode of the SaaS CX Show, I’m talking with Todd Abbott, COO of InsightSquared. This software enables businesses and managers to streamline the biggest time suck – data entry. InsightSquared can take information and distill into processes and best practices, cutting down on analytics substantially. We talk a lot about how his system and AI, in general, can help companies in their quest for a better customer experience.
Overcoming the Data Entry Gap
There are already so many apps available that can create sales analytics- SalesForce comes to mind as a big one. However, most of these programs suffer in the usefulness of their analytics. While you can compile information and get what you need, it’s highly time-consuming and burdensome. In many cases, you have high-level managers and executives spending most of their time on data entry and management, which isn’t an efficient use of their experience and insight.
InsightSquared alleviates this problem by pulling data from various sources and putting sales analytics into customizable dashboards. Even better, each manager can build a unique dashboard to look at the details he or she needs. Now, rather than spending hours inputting data, these executives can use it as a platform for improvement and adjustment.
Using Sales Analytics as a Coaching Tool
Another issue that many big companies have is the disconnect between what the salesperson thinks is happening versus what’s really going on. All too often, sales employees will put too much time and effort into a lead that won’t pan out, just because the lead is responsive or seems interested.
The reason that this approach is a problem is that, like data entry, so much time and energy is spent trying to qualify these leads. A manager may be able to go through the sales process and identify which customers are viable or not, but that’s something the salesperson should do instead.
Now, with machine learning, the system can use history and sales analytics to notify the sales team which leads are lucrative and which ones are a waste. This way, employees can remove a lot of the noise and focus on the sales that matter most. Essentially, the software is coaching a B-level salesperson to be more efficient and proactive.
Machine Learning and the Longer Sales Cycle
While there is a place for AI in a transactional business, where it really shines is in a longer sales cycle. There was a time when a rockstar salesperson could come in and use his or her experience and insight to improve a company’s sales, but now everything is moving much faster. Sales cycles that would take eight months only take two or three, which is why data management is so vital.
As Todd puts it, InsightSquared is much more valuable in these longer sales cycles because there are so many entry points and connections with the client. The longer it takes to close, the more complicated the process, so the software streamlines it along the way by providing the right sales analytics at just the right time.
We talk more about InsightSquared and how sales analytics can improve the customer experience, so check out the rest of the episode here. You can also contact Todd directly at [email protected] or visit them online at www.insightsquared.com.