Customer relationship management is one of the hottest areas in sales management.
Gartner projected this market will reach $36.5 billion by 2017. But despite the massive growth in this space, business owners and sales managers often don’t know what to do with that data once it is accumulated.
This is a waste of money and a lost revenue opportunity. In fact, according to CSO Insights, only 45 percent of forecasted deals are actually won despite the massive enterprise spending on customer relationship management. Doesn’t that seem like a lot of money to be right less than half the time?
Customer relationship management systems fall short when they are based on subjective data from speculative hunches manually entered, often from memory. To complicate matters, most sales teams today are dispersed across multiple locations, making it even harder for managers to gain visibility about team activity.
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Tech companies are constantly innovating to remedy this disconnect by making data easier to sift through or visualize. But do they analyze what a sales rep said to a customer or how they said it?
What sales professionals need in customer relationship management tools is context. That’s where speech analytics come in.
In today’s competitive landscape, it’s not enough to know that sales reps are simply making the right number of calls per day. Instead of focusing on numbers, companies can use speech analytics to measure far more important metrics by tracking what happens after a sales call is answered.
When a business owner integrates speech analytics into the customer relationship management or phone system, it’s possible to target specific keywords and phrases throughout each sales conversation, automatically record them and then see trends and outcomes based on specific language in an activity report. This type of system can also alert managers to conversations during which keywords or emotion detection prompt further review.
From a training perspective, the use of speech analytics is invaluable. Time is money and any weak link on the team can result in lost revenue opportunities. By seeing direct correlations between keywords and outcomes, it’s easier to identify what’s working for top sales representatives as well as what’s not delivering results for underperformers.
For example, managers can intervene immediately if an underperforming agent is varying too much from an approved script. Managers can train reps by coaching them which words to avoid and advising them on selling tactics that work. In this regard, speech analytics have the potential to reduce training costs as much as 30 percent.
Speech analytics don’t end there. There are two more vital benefits for sales managers and business owners:
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1. Prioritizing sales prospects.
When recording every call agents make, speech analytics can track known indicators of high- or low-quality leads such as designated words or phrases, the percentage of silence on a call or the rate of speech and score prospects appropriately.
That lets agents prioritize leads for follow-up, instead of chasing down every lead only to discover most were casual inquiries. Additionally, managers can be notified immediately of a prospect’s competitive mention or sensitivity to fees and other charges.
2. Detecting emotions.
When it’s not the specific words that are causing agents to miss opportunities but rather their emotional state or their reactions to the emotional state of a prospect, speech analytics can quantify otherwise unattainable data.
Tone, rate of speech, volume and silence percentage are all valuable clues as to how an agent has been interacting with a sales prospect and and what additional training might be needed to improve that agent’s outcomes. In addition, if many leads are confused or frustrated on the phone, perhaps there’s a problem with an outbound-marketing campaign. Managers can use data to adjust the campaign accordingly and improve the quality of the leads.
At the end of the day, sales managers can only be as effective as the tools at their disposal, and speech analytics closes the gap between customer-relationship management data and actionable sales intelligence by offering an unprecedented look into sales team activity. Instead overseeing a team with one or two stars, managers can build entire teams of star performers, vastly improving their team’s effectiveness and the company’s bottom line.
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