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TRENDS & INSIGHTS

How to Drive Revenue with a Data-Driven Sales Strategy

By Seismic August 25, 2017 5 min read

The power of data and analytics cannot be ignored – it is how you know what is working, how you can improve, and where there are new opportunities. Everything in the sales organization, from training and forecasting to lead prioritization and sales performance optimization, can be improved with data. While revenue is an important measure of success and the goal every department should be working toward, it’s equally important to understand the metrics that contribute to increases in the bottom line. And while most sales leaders recognize the need for analytics, 4 in 10 B2B organizations are unable to attain meaningful data due to scattered information, and over 50% of executives are dissatisfied with their ability to offer valuable data-driven insights.

What Does it Mean to be “Data-Driven”?

The term “data-driven” refers to what data you gather, how you collect it, how you analyze it, and what you do with those insights. A data-driven sales strategy increases sales rep productivity, offers more objective performance and improvement measures, boosts funnel conversion rates, accelerates revenue growth, improves pipeline visibility, and results in more accurate and precise forecasting.

How to Implement a Data-Driven Sales Strategy

With these types of results, why wouldn’t every organization be data-driven? The problem is that many companies don’t know how to get started.

Read ahead to learn 4 steps to implement a data-driven sales strategy.

1. Equip reps with modern sales tools.

Data is an important aspect of modern sales strategy. And modern sales strategy requires modern sales tools – those technologies that combine predictive and automated capabilities to permit data-driven efficiencies. It’s difficult, if not impossible, to have a data-driven strategy without the tooling in place to gather trusted, accurate, and meaningful data.

Having the right sales technologies to collect and analyze the appropriate data can uncover opportunities for improvement and empower reps with the tools to help them do their jobs more efficiently and effectively. Sales enablement technologies, for example, arm sales teams with the tools and content needed to improve sales execution and drive revenue. Sales leaders can use dashboards to visualize trends and gain valuable insight into rep activity, enabling average performers to replicate the behaviors of top performers.

2. Establish shared organizational goals.

Data is useless unless you are willing to turn it into meaningful insights and then take action. Across the organization, you need the ability to capture data, a strategy for how you will use it (and share it!), and the power to make organizational changes, if merited. This type of plan is essential to keep the sales team performing at or above the level needed to hit hefty sales goals.

Additionally, everybody in the company, from sales rep up to executive, should be bought into a common vision about goals, the strategy to hit those objectives, and success metrics. Gathering data without having a plan in place is just as bad as not collecting data at all. So make sure you have a clear understanding of what KPIs you are measuring, why they are important, how they affect your strategy and sales processes, and how they will affect decision-making practices. Consider what questions you want answered or what problems you want solved.

It’s also important to have a plan in place for organizing the data and making it accessible and utilizable by other departments, such as marketing. This dedication to and transparency of data will help to improve communication across the organization, as well as help to justify decision-making about new processes, restructured budgeting, and additions to the sales stack.

3. Implement continuous coaching.

Data-driven sales guidance uses technology to provide dynamic sales training content and just-in-time coaching, determine which materials are most effective based on the sales situation, recommend best practices to sales reps, and outline next-steps to advance a deal. Info such as kill sheets, talk tracks, persona-based selling tips, and a whole library of content are instantly accessible to reps and proactively recommended in real-time. Further, data can tell reps which pieces of content and messaging are most effective in adding value to the conversation and have proven to help close deals in the past.

Sales leaders can also use data to identify areas for improvement. For example, you can analyze the conversion rates of sales reps at different stages in the sales funnel. Low conversion rates in the bottom of the funnel may indicate the need for additional coaching on closing deals. In comparison to traditional methods, data-driven sales coaching results in faster rep time-to-productivity and shorter sales cycles. And this type of continuous training can yield up to 50% higher net sales per rep.

4. Make data-driven decisions.

Once you have determined key metrics, collected the numbers, and analyzed the data, the final step is to use these insights to guide sales strategy and process. When leveraged appropriately, data and technology can help you scale your sales operations via repeatable methods, optimizations, and continuous improvements.

Consider KPIs such as conversion rates, call rates, win rates, content usage, average deal size, sales cycle length, and deal response time. This info can help answer questions such as “What content and messaging most effectively progress deals and generate the highest ROI?” These data points help sales teams to better understand what factors impact successes and advance sales, how to deliver relevant content at the right time, and what changes will improve rep performance. Such insights allow leadership to be proactive rather than reactive by enabling informed, evidence-based decision-making.

Data offers greater insight into the state of business than ever before, enabling organizations to make informed decisions about next steps for the company. For these reasons, data-driven companies have proven to be both more profitable and productive.

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