Staying updated on the latest sales technology tools is getting harder by the day. It seems that today’s “revolutionary sales app” is obsolete in 30 days. This means, that it’s darn near impossible to understand and deploy the best tools.
Or is It?
We believe that applying a systematic evaluation process can simplify the tool evaluation process. Applying this process can also reveal hidden gems in your existing sales technology stack – saving time and money.
In this post, we’ll discuss how to evaluate your sales technology tools. We’ll also review a 4-part framework for identifying the best tools for your specific organizational challenges.
But before we start, remember: A new tool doesn’t always mean a better tool.
“New” Doesn’t Always Mean “Better.”
Start with a critical look at the existing tools.
Why didn’t they work? Just about every sales organization has some form of Customer Relationship Management technology. Yet adoption – using the tool as intended – for CRM is less than 25 percent.
Maybe the steady stream of new tools masks the less-than-impressive adoption of existing ones. Everything from knowledge management to social selling is available. As you read this, some technology somewhere is certainly in its pre-launch countdown. Who doesn’t want the latest and greatest?
But not so fast. Is it the greatest? This is where sales analytics comes in. Give that shiny new tool a real appraisal. See how it looks then. Will your reps adopt it?
4-Part Sales Technology Tool Evaluation Process
Avoiding the wrong tool is as important as getting the right tool. Evaluate the technology to see if it fits your needs. Sales analytics can be effective for that. They break into four types.
Part 1: Descriptive Sales Analytics tells what happened over the month, the quarter or the year. Will a new tool tell the story better and more descriptively? Organizations are awash in “dirty data” that provide a murky picture. There would be value in an automation tool that clarifies what happened.
Part 2: Sales Diagnostics Analytics reveals why things happened as they did. Facts come into view, making correlation and causality analyses possible. The company can operate from a more objective, data-driven stance. Technologies that can do this exist and might fit well into your company’s toolbox.
Part 3: Predictive Sales Analytics shifts the focus ahead, to show what’s likely to happen. As you’d expect, this area is generating a lot of excitement. Propensity-to-buy formulas are designed to pinpoint when to call on which account. These are in their early stages. But if you find one that works, it merits a closer look. For more about predictive analytics, click here.
Part 4: Prescriptive Sales Analytics is about action. Say your Predictive Sales Analytics shows some likely desirable outcomes. Prescriptive Sales Analytics tells your organization how to reach them. These two forward-looking analytics work together. They show what can be and how to get there.
If a tool moves the analytics numbers, it’s worth considering.
This will help:
Our Sales Tool Checklist was developed to help you determine if the “new” sales tool is worth it. Download it here.
Favor Prescriptive Tools. Carefully Consider The Rest.
Sales reps are not lacking for tools. Tools, though, are lacking for use. Does buying more make sense? If you add tools, you also add sales rep learning curve.
If you are considering new tools, put them through the four analytics screens. Any that survive should have strong prescriptive qualities. Otherwise, the fewer tools the better. Sometimes less is more.