Lead scoring can be done smarter using AI

Prioritising deals involves a good amount of educated guesswork. The mark of an experienced salesperson is knowing instinctively whether a lead will make a deal or not, based on their first few interactions. Using their intuition, talented salespeople are able to assign predictive scores to every deal, allowing them to prioritize their time, energy, and resources.

However, there are some problems with this method:

• How do we quantify experience to create standard numerical scores?
• Different salespeople have different strategies. How can predictions be made when there are multiple perspectives?
• What can salespeople with less experience do to score their leads?

For a long time, there’s been a need for a standardised, intelligent way to perform lead scoring, and CRM vendors have had to scramble to find a solution. To eliminate errors, we need to eliminate the unpredictable human element from the process, while still utilising their natural skills. Based on this realisation, AI was brought in to create a novel solution.

AI excels at prediction

You don’t need a crystal ball to predict whether a lead will become a customer or not. Up until now, lead scoring has been done by salespeople relying on their intuition, which is detached from any objective standards, and limited to those with the most experience. However, with a large, diverse, and comprehensive enough data set, machine-learning algorithms can effectively make predictions from their first day at work.

How is this possible?

Your data holds the key

Your sales data is a goldmine. AI can study it like chess, looking for the patterns your salespeople recognize intuitively. It begins by categorizing touch points, and identifying recognizable triggers, phases, and milestones based on each customer’s journey. This allows the AI to understand how deals are won and lost, developing an effective prediction algorithm. No deal or customer is the same as another, but there are certain signs to look out for in every stage of a sale that indicate its future.

Once the AI is done studying, it can start analyzing every deal in your current pipeline, assigning a percentage for the likelihood of success. Lead scoring, when performed by an AI, is able to follow coherent standards based on facts, rather than intangible experience.

Reiterate your focus

AI-driven lead scoring allows your sales team to focus on their most likely converts first, allowing them to close more deals much sooner, and meet their monthly goals early. When salespeople feel like they’re ahead, they’re more open to taking opportunities that are harder to win. Conversely, lead scoring also ensures that they don’t waste too much time with leads that are unlikely to do business with you.

Nurture your leads

After all the high-ranking leads have been won over by your sales team, what do you do with the rest? Every lead still counts as a learning opportunity. Scores assigned to each lead change with every interaction, allowing you to learn what’s working, and what’s not. If a high-stake deal has a low score, look at it as a chance to build a better relationship. Find out why their score is low, address the problem, and come up with strategies to change their minds.

If a deal’s score has been consistently low despite your best efforts, it’s probably better to give them some space. You can focus on better-ranked leads for a while, giving yourself and the lead some time to think, with the possibility of getting back to them later. The last thing you want to do is spend too much time on opportunities that won’t bear fruit.

Use the right talent for every deal

When you know the conversion score of every lead, you can route them to different salespeople based on their talent and history. Experienced salespeople can take over important deals that might be slipping out of your hands, while rising talents can handle simpler deals, and learn how to sell more effectively.

There can be several factors that drive a deal forward, some of which are better handled by a particular type of salesperson. For example, if your lead is a food truck owner, assigning them to salespeople who are foodies ensures that they both have something in common to talk about. This way, the deal is more likely to get through.

Let go of cold leads

You shouldn’t invest too much of your time and effort on a lead who isn’t responding to your efforts. AI can let you know if a lead is worth pursuing right from the get-go, so that you can keep your sales funnel clear for the right opportunities.

When a lead’s score is consistently low, you need to consider whether the deal is worthy enough to pursue at all. Sometimes, losing a deal is for the best. You can save a lot of time and energy that’s better used on contacts that matter.

Increase employee morale

When your teams know definitively which leads to follow up and which leads to nurture, they’re more compelled to act on them. Wrapping up more of these deals gets them closer to their monthly goals. Therefore, they’ll be more open to working on leads that require more specialized attention, since their self-esteem is high and the pressure to close is reduced.

When your employees are happy with their work, it signals success for your company. No matter how sophisticated AI becomes, it couldn’t ever replace the human touch that drives every sale.

Sound interesting?

Meet Zia, the AI assistant for Zoho CRM. While traditional, clunky CRMs on the market have yet to embrace AI, Zoho CRM delivers AI-based solutions that have yet to be beat. Zia can provide you with lead scoring, allowing you to filter your deals based on historical trends. You can make better informed decisions on lead conversion, nurturing, and distribution with the help of our smart assistant.

AI-driven lead scoring synergies well with the traditional lead scoring style to add an extra layer of credibility to your predictions. Your salespeople’s experience and intuition, combined with Zia’s algorithms and analytics, can do wonders for your sales. Check out Zoho CRM now!