Utilizing data to improve business decision-making, as well as various daily procedures, has produced incredible results for the firms that were first to go seriously into it. All kinds of alternative data types from satellite data to firmographics and technographics have been used by companies to boost their success. Thus, no wonder that firms today aim at a data-driven culture and making as many processes as they can data-driven. One of the procedures that can and has certainly benefited from relying on data is lead generation. Let us look at how data-driven lead generation can be achieved.
What makes lead generation data-driven?
“Data-driven” is now an often-heard buzzword from various business professionals mentioning it as something that they strive for in their companies. However, in most cases, this remains just an ideal that is never to be reached as the concept is not very clearly defined. This leads to stopping way short from actually making a certain procedure data-driven.
Lead generation is a good example, as basic contact information and a few additional facts about a lead is too often considered data enough to label it data-driven. In fact, much more information is needed to be able to honestly grant the name data-driven.
This may sound surprising but truly data-driven lead generation will not be aiming to generate as many leads as possible. It will instead be focused on generating high-quality leads.
Not every lead is a true sales opportunity and being data-driven is what separates such lead generation from the old ways of simply collecting as many e-mails as possible. Data-driven lead generation should lead to possessing enough data to truly qualify leads and send the best of them to sales with enough information to create very potent sales pitches.
Best strategies for data-driven lead generation
Thus, not every procedure declared as data-driven really deserves to assume such a title. So, what sort of methods and practices makes for good data-driven lead generation?
First of all, it is of course data. The importance of having a lot of data has already been mentioned but it stands only presuming that the data conforms to a certain standard of quality. The information about
the lead has to be reliable, that is up-to-date, free of errors and inconsistencies, and as easily workable as possible. Thus, taking good care of the data as well as the databases in which it is stored and accessed is the primal sign of a good data strategy for marketing.
Additionally, data-based lead segmentation and scoring are necessary. Grouping the leads based on their key characteristics will help to identify the most promising segments that sales can concentrate on. And scoring the leads will prepare the sales team even better, allowing them to correctly divide their time and effort among the leads.
Furthermore, a good data-driven lead generation strategy will take advantage of customer profiling. Thus, the data-driven approach should apply not only in reference to the data on the leads but also and even more so in reference to the data on existing customers. Knowing your customer is the first step towards recognizing a good lead for you. Thus, such customer profiling models as buyer persona and ideal customer profile (ICP) should be utilized in lead generation. And for that, of course, one needs to have a lot of high-quality data on one’s customers.
Finally, the data-driven approach to lead generation will allow recognizing where the best leads are coming from and that should also be taken advantage of. After analyzing data on the leads and the various sources, platforms, and social media networks, one should be able to tell which of these produce the best leads for the company. Having this information once again will allow directing the efforts and resources to where they can be used to the best results. In addition, thorough data analysis will produce insights into why one source is better than others and enable adjustments that can bring the worse closer to the better.
Improve efficiency with the right tools
As the final word of advice, it should be said that a good data-driven lead generation model will take all the advantages it can get from the technological developments in the field of data analysis. The main driving force behind the move towards the data-driven approach is the boost inefficiency that comes with it. And when it comes to data, software tools are the efficient choice.
There are various solutions and AI-based tools that help with both data management and data analysis. Utilizing these tools will make the lead generation process faster and in most cases much more
accurate. This will also be cost-efficient as the human workforce can move on to the challenges requiring human intellect and leave the data to the computers that have been created precisely for that.