Data makes the world go ‘round. It also allows for better decision making, enhanced performance, and organic business growth. In fact, research from Harvard Business Review shows data analytics help sales and marketing teams achieve anywhere from 10% to 20% revenue growth on average. So, it makes sense that more and more B2B teams now leverage predictive data insights to identify purchase opportunities faster, especially in the prospecting phase of the sales cycle. The quicker you can pinpoint buyers with high purchase probability, the speedier you can facilitate conversion and drive valuable sales revenue.
But with so many different data types available, which ones should you use to streamline your B2B prospecting efforts? Here are five essential data types to include in your prospecting activities to discover target customers with high-purchase potential:
1. Firmographic data
Firmographic data refers to the organizational details of your target accounts. This includes company-specific information on accounts’ industry type, geographic location, financial health records, growth trends, total number of customers served, and key decision makers.
For B2B prospecting, firmographics offer essential insights to help you kickstart effective prospect segmentation. With firmographic data on hand, you can break down your total number of prospects into smaller, more specialized groups, which allows you to improve sales personalization and prospect prioritization, lending to increased engagement and customer conversion.
How to source firmographic data
There are several ways to source firmographic data for B2B prospecting, and they include:
- Using LinkedIn or other social platforms to gather information
- Searching business directories
- Leveraging contact databases or your CRM
- Purchasing firmographic data from a vendor
Keep in mind, the accuracy of these data sources can sometimes pose a challenge and limit your ability to prospect effectively. Considering how often employees shift roles and leave companies for new opportunities, account contact information isn’t always up to date. However, there are ways to mitigate data inaccuracies, and that includes leveraging smart sales tools with data enrichment capabilities, like Klarity. These tools can streamline your prospecting process even further with solution integration. For example, you can integrate your existing CRM with your sales prospecting tool to capture and record enriched contact data from target accounts. This way, your CRM can exist as the single source of truth for all your prospecting efforts.
2. Technographic data
Technographic data is information relating to an organization’s use of technology products, services, and solutions. It can tell you what kinds of tech tools a company has in its arsenal, details of their implementation, and potential challenges they present.
When you and your team get to prospecting, you can use these insights to craft tailored product offerings that align with the technology needs of your target customers. This sneak peek into buyers’ technology stacks provides the perfect opportunity to prioritize sales efforts and propel the customer journey forward.
How to source technographic data
There are three ways to source technographic data:
- Issue surveys
Whether it’s by phone, email, or through third-party researchers, you can issue surveys to various technology users at target companies. The information you gather will help you develop a deeper understanding of target accounts’ technology needs, challenges, and overall effectiveness.
- Scrape websites for technographic information
You can also use scraping tools to extract detailed information from a company’s website regarding its use of tech solutions. While this method might offer more accurate intel than a self-commissioned survey, it does require some technical know-how to ensure these scraping tools zero in on the most relevant data.
- Partner with a third-party vendor
The most accurate way to collect technographic data is to partner up with a third-party vendor. These companies have the ability to source comprehensive, reliable, and relevant technographic data sets from across the web, which you can then purchase to help streamline prospecting efforts.
These sourced insights give you as much information as possible to develop authentic messaging that resonates with prospective customers’ technology needs. Once a prospect sees you understand their unique business case or concern, you’re one step closer to conversion.
3. Recency data
Recency data is a handy resource in B2B prospecting, and for two good reasons.
One, it allows you to see how long it’s been since an existing customer has made a purchase. If your goal is to drive product renewals or increase cross selling opportunities among your current customer base, then recency data is an excellent metric to gauge how ready these buyers are for another transaction. And two, recency data helps optimize customer prioritization. Statistically speaking, customers who have made a recent purchase, or those who have made multiple purchases over a given period, are most likely to buy again. Therefore, you can prioritize these opportunities over other prospects with less purchase probability.
How to source recency data
Look no further than your customer database to find the purchase recency of your current accounts. Prioritize customers with the most recent transactions, relatively speaking, and note which products or services they’ve purchased. Then, use this information to create an effective cross-selling strategy tailored to these recent buyers. For example, if you notice one of your customers has recently purchased Product A, go ahead and nurture that customer with additional content and customized offerings for complementary products and services.
You can even take prioritization efforts a step further by combining your customers’ recency data with their purchase frequency and total purchase value. This is known as the RFM valuation model. Using the RFM model in your prospecting efforts allows you to assess the purchase behaviors of your current accounts, and it gives you a more definitive understanding of customers’ buying patterns and overall purchase likelihood. Plus, an RFM analysis enables you to identify specific customer segments that will respond best to sales outreach.
Here’s how to calculate the RFM values of your current accounts:
Step 1 – Determine a scoring model
Starting at square one, you’ll need to determine the RFM values of your existing accounts to forecast which ones show the most potential to make an additional purchase. To do this, you’ll need to establish a formal scoring model to numerically valuate the recency, frequency, and monetary purchase values of each customer. Standard practices recommend using a scale of one to five, with five being the highest.
Step 2 – Segment purchase behaviors to create a weighted scale
Next, you’ll need to decide how you want to weigh each numerical value. That’s where segmentation comes in. Simply breakdown each metric by category and assign each one of those categories a weighted numerical score. Here’s an example:
|Weighted numerical score
|Purchase made within a week
|Purchase made within a month
|Purchase made within a quarter
|Purchase made within 6 months
|Purchase made within a year
|10 purchases made in the last year
|8 purchases made within the last year
|6 purchases made within the last year
|4 purchases made within the last year
|3 purchases or less made within the last year
|Purchase value totals over $10K
|Purchase value totals $8K to $9.9K
|Purchase value totals $6K to $7.9K
|Purchase value totals $4K to $5.9K
|Purchase value totals $3.9K or less
If a customer has made two purchases within the last year totaling $11K in sales, and their most recent transaction was made within the last month, then, by this scoring model, the customer’s RFM score would be 154.
With RFM, the higher the score, the more valuable the customer.
4. Engagement data
Engagement data encompasses all the interactions a prospect or existing customer makes with your company through a series of channels, including social media, digital ads, or your own website. If someone fills out a form to access gated material on your site, leaves a comment on a LinkedIn post, or clicks on one of your ads, that person provides key engagement data to help inform and optimize your B2B prospecting efforts. As more prospects engage with your content across the web, the more key insights you can develop to gain a better understanding of buyers’ needs, interests, and business challenges. More importantly, you can leverage engagement data to:
- Target prospects more effectively
- Develop ideal nurtures paths for high-priority prospects
- Identify the most relevant content for target audiences
- Determine channels that generate the most interaction
- Personalize outreach based on prospects’ respective interests
How to source engagement data
You can collect engagement data via first, second, and third-party data sources.
- First-party data:
First-party data is any kind of information you can collect from customers as they interact with content across your company’s own digital properties, like your website, mobile app, and social media accounts. These owned-and-operated systems compile key customer data, like records of digital interaction, purchase history, and preferences, so you can create ads, offers, and additional content catered to your target audiences’ interests.
- Second-party data:
Second-party data is really just the first-party data of another organization, which you can then use “second hand” to gain additional insights on target prospects who have engaged with your company outside your owned channels. For instance, tech companies will often partner with product review sites, such as TrustRadius, Capterra, or G2, to glean critical insights from target prospects beyond their channels’ reach. Second-party data, therefore, is a hugely helpful resource in the B2B prospecting process—it gives you more contextual details on target customers’ needs and interests that you can use to better identify qualified prospects.
- Third-party data:
Third-party data refers to any customer information collected outside your owned-and-operated properties, which means you have to partner with a third-party data vendor to get access. Vendors capture the online activities of target customers across the web, including social media interactions, search histories, and online transactions, giving you a more holistic understanding of your buyer personas. It’s a whole lot of information about a whole lot of people, and when you pair it alongside your first and second-party insights, you save yourself a significant amount of time and resources that you’d otherwise need to collect the info yourself. Typically, third-party data comes categorized into audience segments, which helps you find relevant target accounts and build more detailed buyer profiles.
5. Intent data
Finally, we have intent data—perhaps the most important data metric of them all. That’s because it’s a nifty gauge to determine just how interested your prospects are in making a purchase. The more a prospect shows signs of purchase intent, the more you can assume the prospect is ready for sales interaction. But what kind of activities signal true purchase intent? Here are few examples of how prospects show sales-readiness in the digital space:
- Searching specific keywords related to your product, company, or brand
- Interacting with a chatbot on your website
- Downloading a piece of gated content from your site
- Registering for a webinar or live event
- Requesting a meeting or a product demo
- Researching customer and/or product reviews
Also referred to as “down-funnel” behaviors, these signals indicate a prospect has already progressed far enough in the buyer’s journey to warrant an interaction with sales. And this makes prospect prioritization a much easier lift when you know who’s fit for outreach.
How to source intent data
Similar to engagement data, intent data is also collected via first, second, and third-party sources.
Here are some of the more common channels to find key purchase intent insights:
- Ad platforms
Track the keywords buyers search before they click on an ad. You can use this data to effectively segment prospects based on search interests.
- Search engines
Find out which keywords buyers use when researching your products via search engines. You can use these keyword insights to optimize your website for target customers looking to buy.
- Marketing content
Gather all the engagement data you’ve collected from your content to segment prospects according to topics of interest and/or preferred content formats. You can use these segmented lists to design an effective nurture path for prospects to guide them further along the customer journey.
- Web traffic
Monitor web traffic and click-through data to determine if your website and/or content offers the right kind of information that’s relevant to prospects’ business needs.
- Web scraping
Use website scraping tools to gather information on prospects who have expressed some degree of purchase intent. These insights allow you to create highly targeted lists for effective sales outreach.
- Third-party data vendor
Finally, you can enlist the help of a third-party vendor to aggregate key intent signals from target buyers across the web.
Data-driven prospecting for the win
Want to make B2B prospecting an effective, efficient process for you and your sales team? Easy—put data insights to work. By incorporating firmographic, technographic, recency, engagement, and intent data into your prospecting strategy, you’re better able to connect with target buyers in far less time, allowing you to pad your pipeline with high-potential purchase opportunities.
Curious for some more B2B prospecting tips? Check out our on-demand webinar, “The Blueprint for Better Prospecting.”
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