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How to Prioritize Sales Leads
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Are you prioritizing your sales leads properly? Increase your conversion rates by pitching to the right prospects!

In this article:

  1. Are You Prioritizing Your Business Sales Leads Properly?
  2. Maximizing Your B2B Sales Leads

5 Ways on How to Effectively Prioritize and Organize Your Sales Leads

 

Lead Definition: A person who has provided a set of data (e.g. contact information) that can direct salespeople to a potential customer. This data was generated from a marketing initiative.

Are You Prioritizing Your Business Sales Leads Properly?

Lead Follow-Up | How to Prioritize Sales Leads

While working with sales development teams, one of the most consistent and surprising gaps I see is in their lead prioritization system.

With the teams I’ve worked with, there is a disconnect between how the data suggests they manage their sales leads lists and how they treat their leads in reality.

A study by MarketingSherpa found that 79% of leads never convert to sales opportunities. In a study by Implisit Insights, the gathered data suggest an even smaller amount of conversions, with just 13% of leads converting to opportunities.

Even though data and intuition show that some leads are better than others, the salesforce struggles to effectively prioritize good leads over bad ones. It doesn’t matter if your team is a master at generating sales leads if you don’t separate them into different categories.

Most teams have some idea of what their best lead sources are, but without any guidance, system, or structure on qualified sales leads management, reps spread their marketing efforts equally across all leads.

Today, at the height of both the SaaS and big data revolutions, there’s no excuse for any sales team to go without data-driven lead qualification and prioritization.

The five following points represent proven best practices for qualifying sales leads.

 

1. Immediacy

Lead Response Times Chart | How to Prioritize Sales Leads

In the landmark InsideSales.com study on Lead Response Management, Dr. James Oldroyd found that a prospect filling out a web form is 100x more likely to answer when a rep calls them within the first 5 minutes, as opposed to 30 minutes.

Why does immediately calling prospects result in higher contact rates? You connect with them while they’re still on your webpage and while they’re still interested.

Yet, even though additional studies across the industry have confirmed Dr. Oldroyd’s findings, it’s extremely difficult for sales teams to execute on this data (the average company takes 38 hours to respond to a web form).

While working with sales professionals, I’ve noticed that a common challenge they face is meeting the service-level agreement (SLA) they’ve established with marketing for lead follow-up. With data providing the context/urgency for immediacy and the technology that can automate this process, there is no excuse for breaking a sales and marketing SLA in 2019.

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2. Persistency

The Lead Response Management Study also found that the optimal number of calls per outbound lead was 6. However, on average, reps only dial about 1.5 phone numbers before giving up.

In B2B sales, connecting with decision makers means working your way into the busy schedules of executives. One to two, or even six calls, may not be enough for prospects to know they’re on your radar.

For sales teams, it’s important to improve their calling persistency to boost sales conversions. Although you can use technology for automation purposes, sales teams can enforce processes for increased persistency that require little or no technology by using CRM activities, CRM workflows, CRM systems, or manual processes.

The most important factor for calling persistency is that reps are in the mindset of reaching out to prospects with increased frequency.

RELATED: The Staggering Cost Of Chasing Bad Sales Leads

 

3. High-Converting Lead Sources

Lead to Opp Conversion | How to Prioritize Sales Leads

Sales operations teams have a tremendous amount of data at their disposal. For a sales development team, one of the best pieces of data to consider is lead-to-opportunity conversion by lead source.

Depending on how you compensate your team, you may want to look at slightly different data (e.g., demos per lead source or appointments per lead source).

This data shows which lead sources result in the most valuable and successful contacts: prospects who are ready to move along in the sales cycle.

For example, if your webinar leads convert 30% of the time,  but your trade show leads convert only 5% of the time, then you’d want reps to spend more of their time working webinar leads.

Implisit Insights conducted a study of the most effective lead sources, concluding that website inquiries, customer and employee referrals, and webinars have the highest conversion rates. Email campaigns, lead lists, and events were among the lead sources that resulted in the lowest conversion rates.

Though this line of thinking is fairly intuitive, I’ve seen how difficult it is for sales teams to execute on this data. Ideally, a sales team should use lead prioritization technology to put into place business rules that reflect data-driven best practices.

Sales leaders should implement technology that can help enforce a proven cadence around the highest prioritized leads, ensuring that the team allots their top focus and marketing efforts on high-quality sales leads.

 

4. Artificial Intelligence

Lead Prioritization Model | How to Prioritize Sales Leads

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High-performing sales organizations are recognizing the opportunities of applying AI to their sales process to help them prospect intelligently and eventually sell more.

In order to keep up with intensifying B2B competition and increasingly hyper-aware customers, it’s critical for sales teams to adopt AI as part of their strategy.

There are many helpful lead generation tools currently available in the market. However, many of these tools do not update their scores in real-time and they only take into account a handful of data points.

In addition, these tools often do not include new and recent sales activity in their models.

When looking to apply AI to the sales process, sales leaders should seek a data engine that is dynamic, offers a full view through multiple and varied data sources, and includes sales activities in its modeling.

In addition to vetting a tool for its AI power, it’s important for sales leaders to understand the current limitations of AI in business and within the sales industry. AI models still often require business logic to provide basic success criteria.

5. Data-driven prioritization

To be competitive, your team needs to sell using advanced, scientific methods. This means maximizing data-driven best practices, data-driven business logic, sales leads software programs, and artificial intelligence.

Whether you’re buying sales leads from lead generation companies or getting free sales leads on social media, the goal is to qualify them accordingly. Don’t let your sales reps spend the same amount of effort on bad leads as they do on good leads.

Use data to drive prioritization and, ultimately, fuel sales.

Maximizing Your B2B Sales Leads

What are sales leads and are you running the right digital marketing campaigns? Do you know how to generate sales leads effectively?

Find out how to use AI to improve your lead generation and sales results by grabbing the free guide below.

Predictive Selling Guide | How to Prioritize Sales Leads

 

These are just some of the most helpful tips to help sales professionals qualify and prioritize their sales leads effectively. The main takeaway here is to focus your efforts on prospects that are more likely to buy than those that aren’t. Also, if you want to keep ahead of the industry, you need to maximize the technology available to sales reps today. If you don’t, your business might not survive in the coming years.

What are your questions and clarifications on qualifying sales leads? Post them in the comments section down below!

Up Next: 23 Motivational Sales Quotes To Fire You Up

 

Editor’s Note: This post was originally published on October 25, 2016, and has been updated for accuracy and relevancy.