Predictive analytics is the practice of extracting information from past behavior to identify patterns and trends that will allow future actions to be predicted. In sales, predictive analytics can be...
Predictive analytics is the practice of extracting information from past behavior to identify patterns and trends that will allow future actions to be predicted. In sales, predictive analytics can be used to understand which potential customers are most likely to buy and when.
As a result, sales teams can increase their chances of success while also saving time and money. Organizations can also use predictive analytics to forecast customer churn and identify at-risk customers. Early identification of potential revenue losses allows for action to be taken. This helps organizations prevent and mitigate revenue losses.
For a successful predictive analytics implementation, you need to address the following interdependent factors:
Here are six ways predictive analytics can help sales reps build larger pipelines and grow their businesses:
The most common use of predictive analytics is forecasting. By predicting the future behavior of customers before they have actually made a purchase, sales reps can increase their chances for pipeline growth.
This is important since pipeline growth is often the key metric by which companies evaluate sales reps. The inability to forecast accurately can lead to sales rep turnover.
For example, when an opportunity comes in, a sales rep may not know if it will buy in one month or six months. Alternatively, the opportunity may never turn into a deal. With predictive analytics, sales reps can use past data to determine the likelihood of a future purchase.
This allows businesses to forecast revenue more accurately.
Predictive analytics can also be used to determine new price points and value propositions for underperforming products. For example, suppose that demand for a product is declining because potential customers do not realize its value. In that scenario, predictive analytics can be used to identify the problem and suggest solutions.
Sales reps can learn what types of leads are most likely to buy a specific product or service. This gives sales reps the information they need to adjust price points or value propositions when necessary, increasing their chances for pipeline growth.
Predictive analytics can be used to improve the sales process by refining and narrowing product offerings. Using information gleaned from past customer behavior, sales reps can make more informed decisions about which products are most likely to sell in the future.
They can also identify products or services that are selling well but do not get enough attention. Sales reps can then give these items more attention to maximize pipeline growth.
If sales reps know which products lead to more revenue, they can then adjust their pitches accordingly. This can result in increased pipeline growth over time; opportunities will be more likely to buy from a sales rep using a better product pitch.
Incentive plans and performance assessments can be made more effective when they are linked to predictive analytics data.
By providing sales reps with information about which opportunities are more likely to buy, they can focus on the best revenue opportunities and hit and exceed sales goals. When predictive analytics also informs their incentive plans and performance assessments, this motivates sales reps to focus on the right leads to increase pipeline growth.
Predictive analytics can also help sales reps keep track of their pipeline, allowing them to monitor the progress of deals and make adjustments to maximize growth.
For example, suppose a deal is dragging on for longer than normal. When that happens, a sales rep may be able to identify why with predictive analytics. Then they can make adjustments as necessary.
Data from predictive analytics can also help identify which customers are likely to stay and which are likely to leave. Sales reps can use those insights to take targeted actions to retain potential customers.
This allows revenue teams to develop a plan of action that will mitigate expected losses. Also, early identification can make it easier for sales reps to prevent and mitigate revenue losses in the future.
By comparing historical data, it becomes possible to segment your target accounts based on how engaged they are and how profitable they could be.
This data helps to stay focused on true revenue opportunities and avoid wasting time and money targeting accounts that are not in-market for your solutions. Not everyone in your Total Addressable Market is a buyer — at least not right this moment. We help you focus on the ones who are ready to buy.
Need to boost your sales pipeline performance? Book a demo today to see how pipeline data can help you identify trends, fix weak points, and ultimately grow revenue.