Data-driven decision-making is a powerful way stay ahead of your competitors. The converse is also true. Not using data to inform your sales efforts can mean falling behind.
That’s why sales intelligence - data and insights that help drive sales - are a revenue team buzzword. Learn all about them on this page!
What is Sales Intelligence?
Sales intelligence is the collection and application of data that helps drive sales. This could include company profiles, buying behavior, and details on the industry landscape. It’s everything salespeople can use to make informed decisions while working.
To a lesser degree, “sales intelligence” can also refer to the tools, techniques, and best practices that drive data collection and usage.
Why Sales Intelligence Matters
A clear understanding of a prospect's needs, pain points, and behaviors makes for targeted and compelling marketing. When prospects feel understood, the likelihood of conversions increases through all funnel stages.
Sales intelligence eliminates guesswork and wasted time. It prevents excessive churn, helps us score leads better, and more.
Intelligence can also help refine sales strategies. It can help us understand what’s working and what isn’t. This can create new SOPs, insights, and collateral that closes more sales.
The 4 Levels of Sales Intelligence
The 4 types or levels of sales intelligence are…
- Basic Data Collection. At a foundational level, sales intelligence involves gathering basic company details. This includes prospect names, roles, and contact information. Basically, everything a salesperson would need to reach out to a potential customer.
- Behavioral Analysis. Sales intelligence tools also monitor prospects’ activities. Examples include website visits, email opens, and social media interactions. This data offers insights into customer interests and potential pain points. Sales teams can then use this data to create custom pitches and personalized communication.
- Predictive Analysis. With the help of artificial intelligence, predictive analysis forecasts potential buying behaviors based on a prospect's history and market trends. These details can be used to better understand the sales cycle and predict revenue.
- Prescriptive Intelligence. The final level of data provides sales teams with recommendations on the next steps to take with a prospect. This could be a follow-up email or a product demonstration, for example.
Example of Sales Intelligence in Motion
Let’s use a software company selling CRM solutions as an example. We’ll call them “CRM Force”. CRM Force discovers an ecommerce company tweeting about customer data management challenges.
A quick search through internal data reveals the same company has previously booked a demo with CRM Force. Using the tweet from the data and calls from the demo, a sales rep can reach out with a tailored proposal.
Making the proposal, the sales rep might use AI tuomations to highlight relevant product features popular with ecommerce companies. The result is a highly customized - and likely effective - pitch made using sales intelligence.
Sales Intelligence in B2B vs. B2C
In a B2B environment, sales intelligence revolves around understanding complex organizational structures. Data can also be used to identify decision-makers and determine long-term business goals or challenges.
Insights usually focus on industry trends, company news, mergers, and technology adoption patterns. Sources include industry reports and corporate financial statements.
For B2C businesses, sales intelligence is more customer-centric. It hones in on individual purchasing behaviors, preferences, and motivations. Data sources include social media, online browsing behavior, and customer reviews.
Both B2B and B2C organizations can benefit from sales intelligence. However, the application and sources of this intelligence differ between the two sectors.
