Profitable Sales Intelligence Data Types
Success Quarterly is a tech and business blog that focuses on the intersection of Silicon Valley and Hollywood, including technology, business, mobile, entertainment, media, and related topics.
These days, data and sales go hand in hand. Sales teams can now target their prospects more precisely, completing more transactions, thanks to the vast amount of data accessible.
Data about sales intelligence nowadays comes in a variety of formats. There are several statistics that sales teams may explore, ranging from customer intent to website analytics to competition information.
Here are four types of data sources that every sales team should leverage to increase revenue.
Data from the customer lifecycle
Successful sales teams must have a thorough understanding of their prospects' motives and behaviors. Sales staff must know which talking points to provide when communicating with prospects, from knowing their pain points to the product characteristics they favor.
Customer lifetime data is beneficial in a variety of ways.
For starters, client data assists sales teams in determining what factors contributed to prior offer success. Which pain areas have been addressed, and how are current customers using the solution to do so?
These signals aid salespeople in formulating their first talking topics. Customer feedback and queries from previous contacts may also assist salespeople anticipate resistance from new leads.
Customer lifecycle data helps sales teams discover audience groups and cater to their individual demands if a company's solution base is big. For example, one sector may use a product in a different way than another. In such circumstances, teams must comprehend the various pain areas of these sectors and tackle them appropriately.
The sales process is greatly aided by matching these audience groups to prospects. It becomes much simpler to target individual prospects with the proper offers and anticipate their problems with useful material. Customer lifecycle data, in addition to assisting with prospects, also assists businesses in identifying their most lucrative areas and seasonal sales patterns.
These patterns aid them in effectively allocating resources and developing measures like client lifetime value, which quantify the monetary worth a customer delivers to the organization. These statistics aid salespeople in better understanding their clientele and tailoring their proposals appropriately.
Data from website analytics
Websites are an excellent tool for detecting client intent. They are often the first points of contact between a firm and its customers. Everything from page views to content downloads might reveal a customer's purpose.
Analytics software may provide a wealth of information on how clients act these days. The customer's flow is one of the most essential statistics that sales teams may examine.
What pages did they land on, and what did they do after that? Measuring the amount of time spent on a page and linking it to the pain issues that an audience segment faces might help salespeople figure out what strategy to take with that prospect.
For example, if a user reads multiple blog articles before downloading a gated whitepaper, they're demonstrating a significant desire to compare the product to its competitors. Sales teams may send out email campaigns with product reviews and videos demonstrating the product's benefits.
A high bounce rate or a low number of visits to a page might potentially indicate a problem. Sales and marketing teams may work together to find out what the problem is and how to fix it.
Is the text unsuitable for some demographics, or are the product photos confusing? Is there a need for additional films describing how the product works on the page?
Split tests may be used to assess the efficacy of changes made by teams. Data from analytics assists them in identifying the most effective version for increasing conversions.
Data on the customer journey
Each audience group has its own set of client journeys, which sales people must be aware of. For example, one part may need many approvals from various stakeholders, but another may just have one decision-maker.
Apart from traditional lead capture forms, there are a variety of other options to acquire this information, including chatbots, surveys, and quiz creator tools. Even if you prefer a form interface, conditional logic forms that ask questions depending on prospect replies may be created.
These forms assist teams in better understanding the challenges that the prospect is facing. Of course, to establish whether prospect responses are credible, they must be compared to analytics data.
These responses may expose weaknesses in a sales team's comprehension in certain circumstances. For example, if a prospect does not answer within the specified timeframes after many touchpoints, the sales team may conclude that they are uninterested.
The prospect's decision-making process, on the other hand, may take longer than the sales team had expected. This will be revealed via interviews, and sales teams will be able to change their audience analytics appropriately.
The initial points of contact established by a sales staff can have an impact on customer journeys. Sales teams can better understand which touchpoints support their clients and prospects' journeys by tracking conversions per platform.
Webinars and online events have been quite popular in recent years, and they are progressively displacing in-person conferences. Sales teams may use these tools to track audience participation and develop post-event follow-ups.
A high volume of product feature-related queries during a webinar, for example, indicates a pain area and potential objections during a sales call.
Event participation also helps sales and marketing teams in determining what went wrong and tailoring the next event appropriately. Low engagement may be caused by a variety of factors, ranging from the time of day to the industry's economic cycle.
Teams, on the other hand, may compare engagement to benchmark data to see how effective their event was.
Using signals to close more deals
All of these datasets, when combined, aid sales teams in better understanding their prospects and crafting better experiences. As a consequence, there are more conversions and better income.