Why Most Lead Scoring Systems Fail to Accelerate Sales: Part 4

By on October 2

Continuing with our Digitally Enabled Sales Rep series, today we’re discussing predictive analytics and lead scoring.

Today’s seller is able to target and reach out to far more prospects than ever in the past. Tools like LinkedIn have created the ability to dig into any account to identify and reach out to almost all potential buyers. Data providers allow seamless purchasing of lists dropped right into your CRM.  All of these new lead sources have increased the total universe of potential customers and leads which a sales person can access. With this comes a ton of opportunity for significantly greater sales productivity.

However, most sales people don’t effectively prioritize their activities and are wired to treat all opportunities the same, which means they can waste a lot of time on the wrong accounts/contacts.  The larger volume makes it difficult to prioritize accounts, leads, and contacts.  In order to be successful, it is necessary to focus precious sales time on the right opportunities.

Most companies are trying to reduce this burden on the sales rep by implementing lead scoring (if you are interested in this topic, check our Essential Guide to Lead Scoring.) However, most companies are finding out that lead scoring is not enough.

First – Many lead scores are pretty rudimentary and do not use the breadth of data that can produce a more accurate and predictive result. Lead scores can also be limiting in that the quality of the company target, contact, and lead is packed into the same score.  Because a sales person cannot really understand the score, they don’t trust it and use it.

Second – lead scoring is only as good as the behavior it creates in the sales rep. A score dropped into your CRM without an easy way to support and influence the behavior of the sales rep means the score will sit unused. Enabling the sales rep to use the score and transform a scored lead into a paying customer is key. Most organizations “under-club” this element of scoring.

Predictive modeling can help prioritize the contact most likely to take a call or buy your product/service.  Lead scoring is necessary to help prioritize sales focus, but it is simply not enough.  The best performing sales teams are going a step further and applying predictive analytics across the entire customer lifecycle – from prospect acquisition, to customer nurturing and cross-sell/upsell. The teams are also delivering the scoring to the sales teams using “designed for purpose” user interface technologies to enable the sales rep to take action and drive the ultimate result, more sales.

MarketBridge has a ton of great resources on using predictive analytics to improve sales performance. Check these resources out here and check out part 5 in this series!

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