Tired of lead quality complaints? Data-driven results to the rescue!

You use data and metrics for forecasting sales and qualifying leads. But if your sales team isn’t using data to prioritize which prospects get their attention first, all those quality leads could start looking like losers.

You’re at your wits’ end.

Your sales team is complaining that there aren’t enough high-quality leads in your sales funnel. As a sales manager, you know this is a big problem.

The thing is, you’re at a loss for what else to do.

You’ve aligned with marketing to define your target buyer personas and your lead generation program is humming. The lead nurturing campaigns are steadily helping to increase sales opportunities with less-than-qualified leads. And you’ve got a steady flow of qualified leads going into your sales funnel.

All this data you use to target, nurture, and qualify leads is great. But what happens when you and your team are ready to start selling to leads?

A lead might look great on paper and in your scoring process, but in the real-world selling environment, those promising leads are fizzling out fast. Why?

Consider this statistic from Salesforce: Half of all sales teams say that their forecasting is data-driven, but only a third of sales reps are using data to prioritize leads.

Is your sales team in that 66 percent of sales teams not using data to prioritize leads? If so, it’s no wonder your sales team needs more leads in the top of the funnel in order to meet those forecasted quotas.

Without data insights, maybe your salespeople are chasing dead leads for too long. Or they’re contacting lukewarm leads when they should be going after the hottest ones first. Or they’re not engaging leads at the right time with the right information.

One thing is for sure: deals that should be closing aren’t and your sales reps are getting increasingly frustrated.

It’s time to get on the data-driven lead prioritization bandwagon. Here’s how data can improve your team’s sales process and how you can stop lead quality complaints before they start.

Chase leads while they’re still hot

Take a look at how your marketing and sales teams hand off lead information. How much delay is involved?

If you have automated lead qualification set up for inbound marketing leads but your system takes hours or even days to move the leads over to sales, your sales reps could be missing out on opportunities.

Make sure your lead qualification system is set up to quickly identify and hand off well-qualified leads that have come in through a form. Statistics show that not responding immediately to this kind of lead makes it 10 times less likely your sales rep will close the deal.

Spend less time on leads that are not likely to close

A full six percent of sales reps don’t prioritize their leads at all. Maybe they’re picking where to start at random or pulling names out of a hat?

In any case, not prioritizing leads means your sales reps are relying on the luck of the draw when it comes to where they focus their time. By intermixing leads that are likely to buy with leads that may never buy, salespeople end up spending an equal amount of time on both.

To increase your sales team’s productivity, have your reps prioritize leads based on some kind of data.

You may not have the full capability to do a complete behavioural data analysis. But you can still ensure your sales reps aren’t included in that six percent by at least using demographic data, like company size and job title, and the quality of the email and phone number (is it a direct line or general company mainline?)

You’ll likely already have this data in your CRM, gathered from website forms and other lead generation activities.

Engage leads at the right time

According to Salesforce’s State of Sales, the top two skills sales reps need are active listening and engaging at the right time.

Listening is a human skill and there’s not a lot of room for data to help your sales team there.

Choosing the right times to engage with leads, however, is part soft skill, part hard data. Your sales reps don’t want to wait too long for that first contact with a hot lead. But what if they knew exactly how much time was right for that particular lead?

It’s a delicate dance. One wrong move and your sales reps will be stepping all over their leads’ feet. By analyzing your lead intelligence data, you and your team can see who is ready for contact and who isn’t.

For example, you can use your website analytics data to inform this. Someone who has visited your blog or careers page is probably not as hot a lead as someone who’s visited multiple blog pages, your pricing page, and watched your on-demand product video.

Stop relying on intuition and misreading buying signals.

We all know someone who thinks they have great instincts and won’t consider outside information in their decision-making.

That type of person is probably well represented among the 16 percent of sales reps who prioritize sales leads based on intuition. Seasoned sales reps likely have developed a knack for knowing who to contact first, second, and so on, based on their experience. But if it works, it’s mostly by sheer chance.

Sales reps could be misreading lead signals as ready to buy when they’re not, and vice versa. Using your gut as the arbiter of buying signals could lead to confusion.

For example, a lead might say something that sounds encouraging, like “Oh, that’s interesting.” or “Can you email me some more info?” But, these positive-sounding statements could actually be an incognito brush-off.

A more negative-sounding, “Are there any discounts?” could discourage the sales rep into thinking this lead doesn’t actually want to buy and is just looking for the cheapest price. But in reality, they just wanted to know that they were getting your best deal before submitting your solution for budgeting sign-off.

By using your lead data instead of intuition, your sales reps will have a better idea of how sales-ready the lead is and be able to interpret what they’re saying accordingly.

Know the lead’s propensity to buy

Not all data is used reactively. You can also use ‘propensity to buy’ models to predict a lead’s likelihood to purchase your product.

Using web analytics to track visitors, compare the pre-purchase behaviour of prospective customers against the pre-purchase behaviour of existing customers. What actions do people who buy from you take prior to purchase?

Signing up to receive your marketing emails, visiting more than one blog post, or taking advantage of your free trial offer are all examples of positive activities that can be part of your propensity scoring. You can also include negative behaviours that make leads less likely to buy, like visiting your careers page.

Once you have analyzed the data and identified which behaviours make a lead more or less likely to buy from you, your sales team can use this information to rank leads. For example, say that signing up for your free trial is the number one indicator of propensity to buy.

Sales reps can prioritize leads who are in or just finished their trial period. You could then move leads who haven’t done the free trial into an email nurturing campaign that encourages them to give the product a try.

According to the same Salesforce study, less than half of sales reps have data insights on a customer’s propensity to buy, but of those who do, 85 percent say they find it helpful in doing their job more effectively.

With a propensity score as part of your lead scoring, your sales reps know which leads to focus their efforts on and they can spend less time with leads that are less likely to buy from you.

Backburner low-propensity leads

Leads that are qualified but have a lower probability of closing still should be considered as quality leads by your sales team. You just need a system for putting them on the backburner while they take a slower path toward a sale.

Behavioural data tracking on your website helps your sales reps follow these leads throughout their more drawn-out buyer journey. A data trail means your salespeople won’t have to start over or annoy them with content and information they already have when they’re ready to buy.

Until then, your sales team can “recycle” them back to marketing to join the lead nurturing program.

Conclusion

If you’re not using data to prioritize leads, your sales team is leaving opportunities on the table.

Relying less on gut feeling and more on pinpointing the data that shows your sales reps how to translate good leads into great customers can help fix your lead quality frustrations.