Sales analytics is one of the most flourishing applications of data analytics solutions. In the last three years, its global usage, across a variety of industries, has shot up by more than 40%.
However, sales analytics is not very effective in isolation. While the industry, by 2022, is estimated to create more than $260 billion in value, sales analytics alone cannot achieve that monumental feat.
It works best with data visualization.
What is sales analytics?
Sales analytics is the practice of collecting data and analyzing it in order to forecast sales.
The data is collected from a variety of sources. In fact, the more diverse and voluminous the data, the more refined is the sales analysis. And hence, more accurate is the forecast. The sources include leads, product development data, marketing engagement data, and sales interactions from calls to emails.
All this data is monitored, processed, and analyzed to predict sales trends. This enables sales teams to make more accurate, more well-informed decisions. It enables businesses to readjust their strategy, in accordance, to meet market expectations. In other words, it enables them to always be ahead of the curve.
While it sounds simple, sales analytics, in truth, is deeply complex. However, its rewards undoubtedly outweigh its costs. Sales analytics boosts sales by —
- Powering more accurate, data-driven targeted ads, reducing expenditure
- Listening to customers, informing better product development decisions
- Filling gaps in strategy
- Improving customer retention
- Benchmarking with competitors
- Optimizing sales team performance
How data visualization complements sales analytics
Take a careful look at the benefits of sales analytics.
Every benefit can be split into two parts: learning and acting.
Take customer retention, for example. Sales analytics offers deep insights into the demands and expectations of customers. And this is critical to revenue, as most studies have found that customers expect their favorite brands to anticipate their needs.
However, the insights are only as useful as they are communicable.
It is not enough that sales analytics forecasts sales, that it predicts value or demand, but those insights should also be communicated well to other teams so that they can take the appropriate and effective actions.
And that is all data visualization is about.
Data visualization solutions translate sales trends and insights into graphs, charts, and other representations of data, that make them more accessible and much easier to apprehend. Data visualization reports, in fact, can be tailored for every team, from product development to customer service, so that all teams can act on the insights with minimum friction and maximum effect.
Communication is what connects learning and acting. And the quality of communication, the quality of data visualization, defines the success of not just sales teams but all teams, since they are all deeply interconnected.
Think about it — the communication goes both ways. It is not just sales analytics that informs marketing decisions, but market research and competitor analysis also inform sales decisions. When the communication is first-rate, or data visualization is on point, the transition from learning to acting, between every team, is seamless.
Friction costs time, which costs money. And therefore, communication is key. But what we have rather learned is that data visualization not just complements sales analytics — it complements all analytics.