How a data-driven sales strategy can optimize your conversion rate

Categories Sales
data-driven sales strategy

In today’s B2B landscape, selling only by intuition will not achieve the desired results. To succeed as a salesman, you need data-driven insights. Based on it, you can design your sales methodology that will help you prioritize your leads, optimize your sales cycles, and maximize your conversion rate.

Creating an effective account-based strategy is a step-by-step process. It starts with identifying the best leads, operationalizing the sales process and gradually moving from prospecting to converting.

The methodology can help you think of lead scoring that reflects the current market scenario, realigning the marketing and sales teams. You can prevent the teams from spending too much time on prospecting and instead allow them the opportunity to work with the qualified leads. Let’s take a look at some of the essential requirements that can help in creating an effective go-to-market strategy.

Relevance

The relevance of data is a valuable asset as it helps in identifying best-fit prospects. While instinct can only get you so far as guessing the suitable prospects, the relevant data can help you figure out the potential customers using unique characteristics such as the company’s size, revenue, tech stack, etc.

When you combine today’s advanced technology with an increasingly subtle understanding of the sales cycle, it can be more scalable and cost-effective. It will enable you would be able to capture high-fit targets in your Total addressable market (TAM). You can deploy this relevant data model with the lean, well-calibrated strategy that takes into account the fit score of each prospect. When done accurately, you can even outperform a campaign that targets the unfiltered market.

Purpose

Traditionally, the ability to measure user’s intent stopped at the website. As a sales rep, you would only be able to watch these visitors without being able to influence them. Also, you couldn’t see them beyond your website, and those who never visited would be invisible to you. However, all this can change when you have the data that defines the purpose.

Layering data for purpose with relevant data enables you to figure out where your efforts pay off. If relevant data is about knowing whom to look for, relevant data will help you understand about those who are looking for you. Collecting this type of data is common for sales professionals. By feeding it into sales automation systems companies can build target audiences. It would not only help the sales team know who visited their website but also what they did when they got there.

Engagement

In the context of B2B sales, engagement is about whether a lead watches your webinar or visits your booth at a show. Your sales team can gain valuable information from each attempt the leads make, and use it for initiating a sales conversation or personalizing future interactions. The info on demonstrated behavior can also provide better results when the qualifying these leads.

To make engagement data useful and actionable, you need to graft it with the data for relevance and purpose. Together, they can form a highly valuable collection of information that can be used to create intense brand engagement. It would be in total contrast to the traditional approach that was based on instinct, which was like going around searching for customers in a town with no street names. Now, what you have is a highly detailed cartographical system that would lead you straight to the customers’ doorstep and get them to interact with you.

By using this powerful data-driven marketing strategy, your sales team can spot high-fit leads surging on intent topics related to your business. You can then segment these accounts using customized filters and circle in on highly qualified leads within no time.