The month is coming to an end, you’re struggling to meet your quota, and you still have a lengthy list of leads to call. Which of these leads are most likely to buy, you wonder. If only you could summon hot prospects with a spell and voila, they come flying to you!
If this sounds familiar, it’s time to start prioritizing your leads based on how sales-ready they are. Traditionally, marketers determine an ideal lead based on the CRM data and allocate scores to various metrics such as budget, location, and demographics. For example, you assign 100 points for leads located in the same country, and 70 for a company that is less than five years old. The list is then prioritized on the total score of the leads and passed on to the sales team.
Traditional lead scoring, however, is subjective and prone to human error. That’s because it assumes, without any actual proof, that a metric is relevant to the decision to buy. This is where data science comes to your rescue with predictive lead scoring—an algorithm that uses predictive analytics to score leads. Simply put, it analyzes data in your CRM and the internet to determine which leads are most likely to buy from you.
Predictive lead scoring solutions are have been gaining ground in the B2B sector over the past decade. Here are three reasons why you should use it, too:
1. It’s data-driven: Charles Babbage, the father of computers, said, “errors using inadequate data are much less than those using no data at all.” In plain terms, if you use more data, you make fewer errors. You have a limited amount of data in your CRM about a lead. However, a predictive lead scoring tool will dig through the rich repository of information available on the internet and add that to the data already available about a lead. It’s also adept at identifying patterns and relationships that are not obvious.
For example, you might see that a lot of your customers are from a particular region, like New York City, and assign scores to leads located there. However, using predictive lead scoring might reveal that most of your customers are actually from cities that have a good public transportation system. So the scores should be assigned to any city with a good public transportation system and not just New York City.
With every new piece of data it finds, the algorithm learns and improves itself, becoming more and more accurate over a period of time.
2. It increases sales efficiency: Quite often, the list of leads sales people receive is full of junk contacts who are either not interested in buying or do not have any immediate need for your product. Predictive lead scoring would help you prioritize the list and put the most sales-ready leads, i.e, your hot prospects, on the top so you can stop wasting time on junk contacts.
The key here is to act on the information right away because the metrics can change quickly. Remember, a hot prospect may already be evaluating your competitor. Predictive lead scoring takes ‘need’ of a lead into account. This means a prospect who needs your solution urgently will have a higher priority than others. This makes the sales process faster, thereby improving the sales pipeline.
3. It makes marketing more effective: A predictive lead scoring tool gives you a more accurate picture of your ideal buyer. With that picture in mind, you can refine the marketing pitch and change content on your website and newsletters to address the leads’ needs.
It also helps determine which marketing efforts have worked and which haven’t, so you can improve your overall strategy. Also, predictive lead scoring uses data from both sales and marketing efforts to increase coordination between both teams, thereby improving overall productivity and efficiency.
One of the biggest sources of leads is through your website. With Zoho SalesIQ, you can get a list of all your visitors, prioritized on their lead score.
While there are many reasons to use predictive lead scoring, it is suitable only for those businesses with a good number of leads coming in. Predictive lead scoring is all about data, and if you do not have enough of it, the solution will not work for you. So, if you have just started out, it’s better to follow up on all leads and first build up a database. Once you have a steady stream of leads coming in, go for a predictive lead scoring solution. After implementing the solution, you can see for yourself exactly how much it improves sales and marketing. The proof will be right in front of you. In the data.