Ditch Cold Leads, Use AI Lead Scoring

Publish date:

• 4th January, 2024

For many, it seems mind-boggling how predictive lead scoring coupled with AI allows varied functions across the company, which is proving to be the X-factor.  Budgets are reducing, and sales & marketing teams are under stress to enhance KPIs, scale engagement, and acquire more clients. A recent Salesforce report showed that marketing teams are investing in technologies to increase efficiency and collaboration, with over 63% using artificial intelligence. Lead scoring is simply assigning scores to leads to determine which of them will most likely become a paying client. It is determined by a range of demographic and behavioural factors, and it helps sales and marketing teams comprehend where to devote their time and energy resulting in gains. It is increasingly popular in companies and their concerned teams. The process teams adopt for lead scoring has evolved. Earlier, the team had to review each lead manually and then rank them based on probability and vagaries of human interpretation. It was a slow, cumbersome, and flawed technique say Salesforce services.

Now, lead scoring is a simpler yet more precise science thanks to CRM systems. Combined with marketing automation, companies get access to voluminous datasets like browsing data. This hastened and scaled the process, but not smart enough to distinguish between a website visitor who was surfing and a potential client. At this stage comes predictive lead scoring reveals Salesforce services. It automatically reviews a large cache of data for businesses, factoring in CRM data, behaviour, social data streams, IoT data, and engagement to gauge which prospects will become paying clients. Mix in artificial intelligence, and we are entering a new playing field.

How does it work?

• Predictive lead scoring uses data science and machine learning to review information & confirm shared traits among prospects who converted in the past and the ones who did not.
• It creates and evaluates predictive scoring models to mark the prospects you should prioritise, removing the theory of probability.

Some marketing platforms have built-in lead-scoring tools that state Salesforce services, but businesses may want a different solution for the purpose. Add-ons increase the expense. Einstein Lead Scoring is a leading solution in the market to automate lead scoring. It’s present in Sales Cloud and Marketing Cloud Account Engagement based on whether lead scoring is managed by the sales or marketing team. It drops data into a dashboard with reports that showcase prospect score metrics customised for each business, like average lead score by source, conversion rate by source, and lead score distribution. And it improves with time declare Salesforce services.

The good news about Salesforce is it has a detailed org to enable smart work, and Einstein aids a range of other tasks associated with lead scoring and management. For the sales team, it reveals intelligent account insights, and deal predictions, and creates reminders for follow-up messaging with leads. For the marketing team, Einstein Behaviour Scoring uses a similar model to forecast when leads are going to become paying customers. They also leverage Einstein Insights to maximize campaigns, bond with new audiences, and determine the perfect send time and duration to increase open rates.

Connect with Codleo - Salesforce services for more on how you can benefit from Predictive Lead Scoring + AI duo.

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About the Author

Vineet Rana

Vineet Rana is the digital marketing manager in the #Awesome team at Codleo. He is passionate about all things branding, and his mission is to get amazing content out to everyone as much as possible. When He is not online, he loves cooking, lifting weights, and hiking in the Himalayas with his friends.