With the exponential growth in technology over the past few decades, you’d think that B2B marketing today would be unrecognizable from the good old caveman days without the internet. But all that has really changed is how we do it. Google Ads have replaced newspaper adverts, direct mail is now email and door to door salesmen are now in offices with phones in their hands. Technology has been adopted and not leveraged. If you follow SaaS pundits, they say that the CAC (Cost of Acquisition of a Customer) cannot be more than one-third of the LTV (Life Time Value) of that customer. Marketing is costly, and it is time-consuming. If you are not getting enough leads and conversions, the idea should not be to scale but to use predictive lead scoring and find the right targets because you don’t want to simply spray and pray again. Finding the right target is where a fit score comes in. It is essentially a mathematical representation of how well a prospective customer fits within your ICP (Ideal Customer Profile). Building an ICP is a prerequisite to arrive at a fit score.

There are multiple ways to arrive at an ICP though. After detailed discussions with the sales and marketing teams, we can spec out who an ideal customer is. An example of a well defined ‘ideal customer profile’ would be, an enterprise or a mid-market company in the US making over $5 million a year or long tail companies with less than 10,000 unique visitors a month, who are just about to break out. Another way of arriving at an ICP is by analyzing the CRM data using a platform like PipeCandy, to figure out what type of companies convert, how fast they convert, and which ones will have a higher LTV. Once the ICP has been decided on, a predictive lead scoring platform can analyze it and create a list of the companies that would be a perfect fit.

  A fit score is not binary. It doesn’t simply qualify companies as “fit” or “not a fit”. It is generally a score between 1 and 10 with 10 being the perfect fit. Some companies do ‘fit scores’ like they are heatmaps (High, Medium, Low). Personally, we’d prefer the granularity of a number. This lets you decide how to treat leads and decide how much money and effort goes into acquiring each one. For companies with scores between 8 and 10, which are very high fit companies, you should not be sending mass email campaigns. If they are large companies, the right approach would be ABM (Account Based Marketing). By engaging with them on different channels and through different people at various levels of your organization, you can build a relationship with them. For smaller targets who are a high fit, you can form an association by inviting them to attend a webinar, meeting them at conferences and even engaging with them one-on-one. While high fit companies are essentially the big picture, there is always an appetite for popcorn. Companies with scores between 5 and 7 are still good prospects though not an exact fit or could be nurtured towards a buying decision sometime in the future. It’s definitely worth starting a conversation with these companies through email or retargeting because they either exhibit some of the required characteristics from the ICP or they will at some point become a high fit. This is not the only application of a fit score either. They can be used to qualify leads at the top of the funnel and help you decide which prospect needs how much work. You can also create ‘custom fit scoring models’ for predictive lead scoring to find cross-selling and up-selling opportunities with existing customers. There is no doubt that a fit score is quite useful. But even after my 700-word flowery recommendation, the reality is that it’s not enough on its own. A fit score along with what is called an ‘intent score’ is the best way to streamline marketing and sales efforts and find the best accounts to close. And now I shall make my exit, TV episode style. I’ll get into what an intent score is and how it compliments the fit score in my follow up article next week.