Building Intent Data into Your Sales Enablement Process

There are plenty of challenges working against your hopes of contributing to the sales pipeline.
Companies that are in-market to buy your products aren’t considering your brand. Content fails to generate sales conversations. Target account lists remain static and ignore lookalike companies that might show intent. Company intent can’t be tracked to specific contacts for sales to engage. The list goes on and on.
Working with a third-party intent data provider might seem like a magic bullet solution to these problems. And while intent data is certainly valuable, your investments will be wasted without a strategy for getting the most out of it.
Improving sales enablement and contributing to your company’s pipeline starts with a set plan for intent signal scoring.
4 Main Categories for Intent Signal Scoring
Much like lead scoring, intent signal scoring adds a concrete value to individual contacts, prospects, and/or accounts that correlates to their stage of the buyer’s journey. However, the marketing qualified leads (MQLs) that come out of traditional lead scoring often fall short of sales expectations.
Sales enablement won’t succeed if the MQLs you deliver aren’t actually on the path to making a purchase decision. That’s where intent signal scoring comes into play. By adding the context of purchase intent, you can help sales engage with buyers more effectively with personalized content and messaging.
But intent data only adds value when you can accurately apply a scoring model to your prospects. Whether you’re creating these scores manually or with a predictive model, there are four main categories your intent signal scoring should focus on in a 100-point scale:

Awareness Stage (0-30): These are your top of funnel contacts that may have read blog posts or read pages on your own website. But with third-party data, you can gain insight into buyer behavior on competitor and industry websites. Unlike traditional lead scoring, intent signal scoring ensures that your awareness-stage contacts are only those that fit your target profiles as opposed to high-volume, low-relevance contacts.
Nurturing Stage (31-60): This is the next level of marketing engagement in which accounts may download informational content, subscribe to a newsletter, or show repeated interest in your own web pages. At this stage, third-party intent data providers can provide more granular insight into behavior by analyzing billions of web interactions and using natural language processing to index keywords that map to your product categories.
Consideration Stage (61-80): With traditional lead scoring, this is where you might hand things off to sales. But this puts a lot of pressure on sales enablement and might take up valuable resources that could otherwise be spent closing deals. In this range, you’ll want to focus on using data to target ads, create personalized research content, and syndicate your messaging to remain top of mind with contacts that are showing greater purchase intent.
Action Stage (81-100): This is the stage where you want to make the handoff to sales. When accounts are showing this level of intent, they’re ready to make a purchase and should be in contact with your sales team to make the final decision. When you’re able to send qualified leads to your sales team with this level of purchase intent, you’ll be able to overcome many of the typical issues that cause disconnects between your department and theirs.

When you can accurately place prospects in these intent scoring categories, you’ll be able to maximize the efficiency, quality, and win-rate of your pipeline. Those benefits are the direct result of formalizing sales enablement processes and ensuring that all resources are applied directly to companies that are in the market to buy what you sell.
The real challenge is applying all of your intent data effectively to ensure these scores are accurate.
Automating the Intent Signal Scoring Process
The best way to maximize the accuracy of intent signal scoring is to automate the process and take advantage of a predictive model for assessing behavior.
Trying to manually assess intent will lead to the same issues that traditional lead scoring has always presented. But when you work with a third-party intent data provider, you gain access to billions of data points and advanced algorithms that can accurately predict when leads become ready for sales.
The first step to success is knowing that not all intent data is created equal. When you can look beyond the promises of third-party providers and understand what you’re really investing in, you’ll be able to get the highest possible ROI.

There are plenty of challenges working against your hopes of contributing to the sales pipeline.

Companies that are in-market to buy your products aren’t considering your brand. Content fails to generate sales conversations. Target account lists remain static and ignore lookalike companies that might show intent. Company intent can’t be tracked to specific contacts for sales to engage. The list goes on and on.

Working with a third-party intent data provider might seem like a magic bullet solution to these problems. And while intent data is certainly valuable, your investments will be wasted without a strategy for getting the most out of it.

Improving sales enablement and contributing to your company’s pipeline starts with a set plan for intent signal scoring.

4 Main Categories for Intent Signal Scoring

Much like lead scoring, intent signal scoring adds a concrete value to individual contacts, prospects, and/or accounts that correlates to their stage of the buyer’s journey. However, the marketing qualified leads (MQLs) that come out of traditional lead scoring often fall short of sales expectations.

Sales enablement won’t succeed if the MQLs you deliver aren’t actually on the path to making a purchase decision. That’s where intent signal scoring comes into play. By adding the context of purchase intent, you can help sales engage with buyers more effectively with personalized content and messaging.

But intent data only adds value when you can accurately apply a scoring model to your prospects. Whether you’re creating these scores manually or with a predictive model, there are four main categories your intent signal scoring should focus on in a 100-point scale:

  • Awareness Stage (0-30): These are your top of funnel contacts that may have read blog posts or read pages on your own website. But with third-party data, you can gain insight into buyer behavior on competitor and industry websites. Unlike traditional lead scoring, intent signal scoring ensures that your awareness-stage contacts are only those that fit your target profiles as opposed to high-volume, low-relevance contacts.
  • Nurturing Stage (31-60): This is the next level of marketing engagement in which accounts may download informational content, subscribe to a newsletter, or show repeated interest in your own web pages. At this stage, third-party intent data providers can provide more granular insight into behavior by analyzing billions of web interactions and using natural language processing to index keywords that map to your product categories.
  • Consideration Stage (61-80): With traditional lead scoring, this is where you might hand things off to sales. But this puts a lot of pressure on sales enablement and might take up valuable resources that could otherwise be spent closing deals. In this range, you’ll want to focus on using data to target ads, create personalized research content, and syndicate your messaging to remain top of mind with contacts that are showing greater purchase intent.
  • Action Stage (81-100): This is the stage where you want to make the handoff to sales. When accounts are showing this level of intent, they’re ready to make a purchase and should be in contact with your sales team to make the final decision. When you’re able to send qualified leads to your sales team with this level of purchase intent, you’ll be able to overcome many of the typical issues that cause disconnects between your department and theirs.

When you can accurately place prospects in these intent scoring categories, you’ll be able to maximize the efficiency, quality, and win-rate of your pipeline. Those benefits are the direct result of formalizing sales enablement processes and ensuring that all resources are applied directly to companies that are in the market to buy what you sell.

The real challenge is applying all of your intent data effectively to ensure these scores are accurate.

Automating the Intent Signal Scoring Process

The best way to maximize the accuracy of intent signal scoring is to automate the process and take advantage of a predictive model for assessing behavior.

Trying to manually assess intent will lead to the same issues that traditional lead scoring has always presented. But when you work with a third-party intent data provider, you gain access to billions of data points and advanced algorithms that can accurately predict when leads become ready for sales.

The first step to success is knowing that not all intent data is created equal. When you can look beyond the promises of third-party providers and understand what you’re really investing in, you’ll be able to get the highest possible ROI.

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