Buyer Intent Data: Identify and Prioritize Sales-Ready Accounts

 

 

It’s no secret that B2B marketing teams are being held accountable for their influence on the pipeline more than in the recent past.

B2B marketers need an efficient approach to make every dollar count toward revenue.

In fact, surveys about the most significant changes in the role of the CMO find that now 47% of CMOs are expected to demonstrate their bottom line impact while as many as 40% are expected to prove marketing ROI with superhuman speed.

However, with limited budgets, erratic markets, and growing competition, this is easier said than done.

Accordingly, this article explores why buyer intent data may be the answer to pragmatic, revenue-centric marketing going forward.

What is intent data?

B2B intent data consists of “signals” that determine customer behavior and purchasing propensity based on engagement captured across marketing, sales, and financial touchpoints.

As a marketer, you can take advantage of these intent signals to identify and prioritize a subset of sales-ready accounts above cold, generic accounts.

For example, a user who repeatedly visits the pricing page tells you that they’re moving through the sales cycle by comparing prices across alternate solutions. We can safely assume that prioritizing this account over a cold one will result in a better chance of conversion.

Whether it’s page views, button clicks, firmographics, financial trends, hiring patterns, or anything else, you have several types of intent signals to think about, each reflecting a specific consideration in the purchase decision.

In short, intent data zeroes in on otherwise hidden intentions to wring out every last bit of ROI from existing marketing and sales efforts.

In other words: more pipeline from existing spend.

What are the benefits of intent data in sales and marketing?

When put to good use, intent data provides tremendous value to marketing teams.

1. Better resource allocation and lead prioritization

The truth is, not every company in the world makes a good fit for your product.

In fact, only a fraction of accounts that go to your website, engage with your ad campaigns or interact with your customer reviews are relevant to your business. Out of this, an even smaller subset of accounts are immediately ready to buy.

Intent data reveals that sweet set of sales-ready accounts, which in turn empowers better account prioritization and resource allocation. Instead of casting a wide net to capture uncertain demand, marketing teams can direct spends toward accounts that show explicit intent.

This leads to improved conversion rates, higher return on ad spends, and reduced CACs — much better results than what you get with broader “spray and pray” tactics.

2. Improved website conversion

Just a few years ago, companies were ready to purchase new software at the drop of a hat. Today, the market is far more conservative. Larger buying committees, longer sales cycles, and lower win rates all point to this.

Accordingly, accounts that are already engaging with your website become much more valuable. However, only about 4% of these website visitors generally convert via signups, and the majority of traffic continues to remain anonymous.

In tandem with a reverse IP-lookup tool, intent data can identify, qualify, and double down on otherwise hidden opportunities from website traffic.

Here are a few examples:

• Retargeting accounts that visit paid landing pages but fail to sign-up
• Reaching out to accounts that read BoFu competitor comparison blogs
• Following up with accounts that fill out a demo form but don’t submit it

Intent data and account intelligence act as nets that prevent valuable opportunities from slipping through the cracks, thereby improving conversions from existing website traffic.

3. Identify buyers and potential leads faster

Research finds that buyers are nearly 60% of the way through the customer journey before they make contact with sales. This means that by the time an account submits a form, their opinions, preferences, and concerns have already started to crystallize – for better or worse.

Intent data finds serious buyers far earlier along the customer journey so teams can beat their competitors to the deal by establishing evaluation criteria and nurturing key relationships before anyone else.

For example, let’s say a buyer is evaluating two vendors: vendor A and vendor B. The buyer visits both vendors’ websites and peruses their features, pricing, and use cases. Vendor A uses this intent data and immediately starts retargeting the buyer with case studies and testimonials, while vendor B continues to remain unaware of the buyer’s interest.

A few weeks later, the buyer submits a demo form for both tools. By that time, vendor A has already built a favorable rapport and vendor B has only just started nurturing the relationship. There’s no doubt that in this case, all else equal, vendor A is more likely to close the deal.

4. Better account-based marketing (ABM) personalization

In addition to identifying which accounts are engaging with your brand, intent data also highlights what they’re engaging with. Which blogs are they reading? Did they download privacy documentation? How about whitepapers? Did they view product pages? Have they been going through G2 reviews?

Answering these questions can act as a proxy for buyers’ interests, pain points, and use cases. Rather than relying on intuition alone, intent data becomes a light, guiding you as you craft marketing messaging and sales outreach that will truly resonate with your target audience.

Types of intent data

As previously mentioned, there are several types of intent data and buyer intent data providers — each of which provides a unique angle on a customer’s purchase intent. They can be summarized as follows:

1. Zero-party intent data

Data collected directly from customers via form submissions, mail communication, discovery calls, etc. This is data that customers intentionally and deliberately choose to share, including:

• PoC name and contact details
• Self-attribution information
• Customer requirements, budgets, etc.

2. First-party intent data

Data collected from a customer’s direct interactions with a business. This data is captured upon consent from a visitor.

First-party data can include:

• Page views
• Mail opens
• Button clicks
• Scroll-depth, etc

3. Second-party intent data

Data collected from another business’ first-party data. Again, this data is captured upon consent from a visitor. Second-party data includes:

• LinkedIn ad impressions
• G2 product page interactions
• Google’s search console data

4. Third-party intent data

Data collected from aggregated intent data vendors. This can include:

• Technographic details
• Firmographic details (Company industry, size, revenue range, etc)

How to use intent data

Now that we’ve gotten the whats and whys out of the way, let’s dive into the how.

While there are several ways to approach intent data, we’ve focused on the following intuitive, four-step process that has brought us great, scalable success.

The first two steps require a strong data foundation across engagement data, firmographics, and technographics. Reviewing the tools used to support this foundation is beyond the scope of this article, but there are several robust options available.

Step three involves enriching the most important, sales-ready accounts, while the final phase targets the right people within those accounts across channels. Let’s get started!

1. Identify

Use an IP-based account intelligence tool to identify anonymous accounts that visit your website, but don’t take any other actions. This gives you a starting point, a set of accounts that are, at the very least, aware of your brand. You likely already have better leads to target than completely cold ones.

That being said, it’s unlikely that each one of these accounts will make a good customer fit. Some may be too small, others too large. Some may be from an industry you don’t cater to, while others may be from geographies you don’t serve.

Once you clock these accounts, start filtering them down to high-fit accounts that match your ideal client profile.

2. Qualify

At this stage, you have a list of brand-aware ICP accounts. In theory, selling to any of them would be a good idea because each one would make a sensible fit for your business. However, within this subset of accounts, some are more sales-ready than others.

While Account A might be in the awareness stages of the customer journey, Account B might have already completed the majority of its research and hang around the consideration stage.

Measuring engagement and qualifying accounts based on their sales-readiness is the next step of the process. Admittedly, this involves a qualitative scoring approach that may not always yield predictable results. The B2B customer journey is, after all, a fickle, non-linear process.

There may always be outlying cases when an account lands on your website for the first time, immediately books a demo, and becomes a customer right after. This is rarely the case. In general, you find a strong correlation between engagement and intent.

Capitalize on this correlation.

Use what you know about first-party and second-party intent data to discern account engagement across your website, ad campaigns, and G2 pages. Analyze which pages accounts go to over and over again, how much time they spend on each page, or which buttons they click to gauge interest.

Here are a few examples:

• An account that repeatedly views the pricing page likely has more purchase intent than an account bouncing off a ToFu blog after a few seconds
• An account that’s comparing product features and reviews on G2 after viewing an ad likely has more purchase intent than an account that has taken no relevant action after viewing the same ad

Source: Factors.ai

If you’re wondering how to capture this relatively nuanced data, it’s worth checking out account intelligence tools that automate the collection and qualification processes.

Set your qualification criteria and filter down your initial list of ICP accounts to a list of high-intent ICP accounts. This is where you find tremendous low-hanging opportunities.

Rather than spending marketing dollars on generating brand awareness and driving fresh traffic, the majority of your budget should be directed toward capitalizing on this set of accounts.

3. Enrich

At this stage, you have a list of high-intent ICP accounts to target, and now, you’ll have to reach out to real people within these accounts. This step involves using a contact database to collect contact details of the people you want to target with campaigns and outreach.

Who you’re reaching out to depends on the nature of your product.

Marketing technologies want to reach out to marketers, accounting software makers want to pitch to finance teams, project management tools want attention from project managers.

The bottom line is this: regardless of the nature of your product, make sure that you’re reaching out to multiple stakeholders within each account, such as end-users, managers, and financiers.

We can’t overstate the importance of holistically targeting accounts. Account-level targeting creates a significant sense of urgency and awareness of your product throughout the breadth of the target account.

The purchasing decision is in the hands of several stakeholders, not just one with unyielding influence. This is all a result of your comprehensive, overarching target strategy.

4. Target

Finally, we come to targeting. You know which accounts you’re targeting and who you’re targeting within each account. Now, it’s once again time to use the intent data you picked up in the initial stages.

Determining the answer to these questions provides insight into what each account cares about, giving you valuable context into what sort of messaging resonates best.

So when you find an account that spent time on the product comparison section without submitting a form, you’ll know that a LinkedIn creative around product comparisons might help.

An account visits your product listing on G2? An outreach email, along with testimonials and case studies, might be relevant. Or if an account visits a paid landing page but is yet to convert, you’ll know to prioritize them for your next sales call over a completely cold account that hasn’t expressed any intent.

Source: Factors.ai

There’s no hard and fast rule to effective retargeting. But picking up on these subtle intent signals and experimenting with messaging based on an account’s previous engagement almost always results in positive results.

Source: Factors.ai

A month-long experiment that compared LinkedIn ad performance between intent and non-intent campaigns found that all else being equal, intent-based marketing results in more impressions, clicks, and, most importantly, more leads (SQLs) from the same amount of money.

Navigating the intent data landscape: opportunities and challenges

And there you have it. Intent data is an incredibly powerful tool for marketing and sales folks who want to derive more value (read: pipeline) from existing efforts. It’s a matter of identifying accounts that make the most sense to sell to, prioritizing them based on their readiness to buy, and targeting the right people with the right message from those accounts.

Et voilà – more pipeline without spending a dime more than you already do.

That being said, using intent data isn’t perfect. For one, acquiring high quality intent data can be tedious and time-consuming. As customer journeys become increasingly fragmented, capturing intent signals across events, websites, customer reviews, and ad campaigns is no mean feat.

Moreover, making sense of the data that’s been collected can be tricky as well. Is a pricing page visit a greater sign of intent than a product page visit? How long should a visitor spend on a blog before they can be considered intent-worthy? How many different touchpoints should an account make before we consider it sales-ready?

No fixed answers to these questions exist. Instead, make it a priority to consistently experiment with different intent parameters and engagement criteria until you find a system that works repeatedly. It’s also worth fine-tuning this system on a regular basis as external factors, like market conditions, competition, and customer preference, continue to evolve with time.

It’s worth sticking to a few (3-4) simple types of intent signals rather than evaluating dozens of them simultaneously. This goes double if you’re just starting out. More often than not, it’s the quality of intent data that’s more valuable than the volume of intent signals.

While the value is unequivocal, the degree of use you get from it depends on how you go about implementing it. At the end of the day, all the intent in the world is insufficient unless your foundation for the basics of marketing – copies, creatives, channels – is sturdy.

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This article was written by G2 and originally published here.

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