Buying Signals: 2 types of B2B intent data. 3 steps to use
11 min

Buying Signals: 2 types of B2B intent data. 3 steps to use

The concept of Buying signals is getting more common for revenue teams to implement in everyday processes
March 3, 2021

Who should use B2B intent for marketing operations and common challenges

First of all, we need to understand if any surge exists in our category. Currently, buyer attention is very limited and your market may simply not generate any buyer signals from direct search. It may not be correct estimation of a full customer journey.

B2B customers are very different from B2C.

Even if during a customer journey prospect may browse some data for detailed insights, frequently qualified leads do not have enough budget even close.

In the era of YouTube, free-to-play, and very short content consumption timelines, many people can create noise with no real change to become a qualified leads.

We need to see if this increase in demand has a direct correlation with our offering to trigger a sale. If you are trying to build a new category, a new product, it might be challenging to clarify if the intent for your product is real for target accounts.

For example, you have the product in the cybersecurity category. You believe that person consuming content about cyber attacks and threads is a great potential customer.

The problem with intent signals for the target list will be that it is unusual for prospects to consume any such content in the past. So any slight increase in consumption will show high intent for prospective accounts in cybersecurity topics.

However, cybersecurity is a broad niche. Real buyer intentions may be very different from your opinion. The case company searched to protect their email servers from spoofing, and fraud is more frequent than multi-level security on data collection of sensitive data, etc.

If the category is broad and your product quite niche and new, we suggest focusing more time on your direct pitch and messaging vs. using intent data signals which can highlight you wrong B2B companies.

In case you have a strong category and clear market leaders, and consumer knowledge of problems, you can start relying on external intent. The content consumption will be more targeted and precise for your data vendors to structure and present a strong buyer through intent signal.

An example of such battle can be the "conversational marketing" category -

There are a few leaders in the market, like Drift or Intercom, and a very long tail of other marketing solutions similar to them.

With low average ACV and LTV, market leaders generate many specific niche content and educational materials, so even more thought leaders, software providers, consultants, and agencies post on relevant topics.

All there creates an apparent buying journey for potential buyers from the Awareness to Purchase stages. As a result, an opportunity to catch online behavior and activities related to Awareness and Consideration steps is high! Marketing teams miss an excellent opportunity to leverage alternative data to capture usually invisible demand from potential leads.

We believe most future marketing campaigns will launch with clear signals on what Job Titles from Ideal Customer Profile wants.

Category creation is complex, expensive, risky, and time-consuming activity, where it is hard to leverage intent data.

However, the following market players can use relevant insight and multiple levels of context generated by experiences created long before them.

They can enter the industry with such knowledge, build an ideal target companies list much better, and shorten the ROI-positive investments cycle.

Timing, Relevance, and Personalization keep being the main parameters of successful opportunity creation and deal closing.

To fight these challenges, a lot of technologies emerged in marketing and sales operations.

One such approach is the concept of Buying signals -

The message company or person creates that shows his increased interest in a categories of topics, which allows selling him a solution to this problem.

Since the concept is vast, we can break down it into several categories, such as

  • Company Data Updates
  • Contact Data Updates
  • Strategy Data Updates
  • Financial Data Updates
  • 1st Party Engagement Data (internal intent data)
  • 3rd Party Engagement Data (external intent data)

Some of the signals might seem to be straight-forward, like

  • An increase in company headcount in the IT department shows buying signals for project management software.
  • Change in contact title signals new position and opportunity to get referral sales on his new place.
  • Each publicly working company is posting a 10-K report and present a strategy update for a new year.
  • New successful fundraise often spend on the increase in marketing/sales headcount and significant investments in related technologies
  • 1s party data is about the tools you own and can collect data like your website or app. When a user is looking at your pricing page and logs in to your product each day, it shows a high-level buying signal
  • When a potential lead reviews related products and industry topics to your solution on multiple websites and social media, it creates a clear buying signal to connect and propose your product.

The last point is an example of a B2B Buyer intent data signal generated from 3rd Party sources (external intent).

Let's break more into these Intent Signals and data sources to understand better how Sales teams leverage their power.

Types of External intent data in the Buying process

Here are some most common examples of external intent -

  • Increased interest in social pages, articles, posts, etc., in a particular segment from sources you do not own.
  • Export of gated content from the niche communities as an example of third-party intent data
  • Engagement on digital ads in a similar category collected from account-based marketing software

Since the topic attributes consumption viewed as "average" or "normal" per each company may be different, the real intent which marketing teams can use to improve buyer journey is calculated most frequently in the form of a surge score -

Surge score shows how today's demand or intent in topic consumptions differs within the list of target accounts compared to the previous period.

With the increased adoption of marketing automation platforms and tech, passive first-party data collection through cookies is rising. It gives a tremendous opportunity to save, structure, and analyze behavioural signals.

Most intent data providers buy such first-party intent data to allow B2B marketers advanced methods to reach out to prospective buyers.

How to leverage 1st and 3rd party intent data for marketing and demand generation teams

So, how can we implement this data in current times into our B2B buyers process?

There are a few most common ways to use such data -

  • Scoring
  • Trigger-based workflows
  • Anonymous Personalization

Scoring Accounts / Contacts

Any demand generation team and sales reps want to know whom to target today to hit their quarterly and annual goals.

Some have a target list of accounts to follow, some have clear Buyer Personas with a shortlist of titles and nailed go-to-market messaging, some spend time with the flow of incoming requests.

However, they want to focus on the target audience with the shortest sales cycles and highest LTV.

In that case, intent data can play an essential role in pre-build scoring workflows to get contextual insights for inbound leads.

You can build a matrix of points to add and decrease based on several data factors to consider in your scoring matrix, like

Parameter Score
Website visit -> pricing page (1st party data) +5
Website visit -> relevant blog content (1st party data) +3
1st party Content Download (1st party data) +5
Email Engagement - opens / replies (1st party data) +10
Your LinkedIn content Engagement - likes, shares, comments (1st party data) +10
Similar to Yours LinkedIn content Engagement - likes, shares, comments (3rd party data) +5
New relevant hirings (3rd party data) +5
Relevant changes in leadership (3rd party data) +5
The surge in target content consumption (3rd party data) +10

As a result, an account that

  1. consumes a lot of content about account-based marketing
  2. showing increased engagement on LinkedIn posts on this party topic
  3. hiring for relevant roles (like the head of the ABM department)

has similar chances to be on the top of your prospect list as a company that

  1. visited your blog
  2. downloaded your content
  3. opened your sales / marketing emails a few times.

Finally, if this intersects, you get a list of accounts that are even more likely to buy based on these personal insights cause they engage not only with your content and with public space.

Why is it important? You don't want to spend precious time on a company that engaged some time with your content, ghosted you, and hasn't shown any public interest in the problem you try to address.

At the same time, markets are constantly changing. You don't want to miss a new trend/need in the segment you haven't thought of. Focusing only on first-party data can limit your vision of the market, its needs, and real insights. Adding some alternative data from 3rd party sources about buying signals will help you create a better picture of the whole market.

Trigger-based workflows

Have you ever get ads of products you just searched on every other content platform? That is only one example of a trigger-based workflow. When you sign-up for a product and start receiving some product updates, news, knowledge sharing content, that's another example.

Similar to all standard workflows, we can build demand generation plays with intent data.

When your target prospects start searches for relevant content on 3rd party sources, you can launch a targeted marketing campaign based on this events on the account level in LinkedIn.

When you revealed anonymous IP as a relevant account on your website that is browsing your pricing page or blog posts, you should try to launch retargeting campaign just for them and assign a sales rep to prospect that company.

When the company starts searching for a VP of marketing with knowledge of HubSpot, let's launch outreach sequence and account-based ads showing how our product brings value to marketing professional fully integrated with HubSpot.

Finally, when a company shows a surge in topics like "conversational marketing," you know about their increased interest in products similar to Intercom or Drift. Having complementary goods creates a positive outcome for all parties, while having pure substitutes will give you higher chances to win a new customer.

The most important, the final beneficiary is our prospective customers will get the most value and the best service based on these insights.

Anonymous Personalization

Each buyer has his unique journey. In 2021, Google hasn't updated its policy for 3rd parties cookies yet. As a result, we as B2B consumers have an excellent opportunity to experience a high personalization of websites we visit based on our content consumption, preferences, and current employer.

How does it look like for us as consumers?

If you work in the recruitment sector and see some professional wording on the home page, particularly for your industry, it is a sign of applied personalization. Also, you should try to implement intent data for your content marketing strategy! Capture online activity based with right buyer context is an ultimate goal of any B2B marketing and sales leaders! Also, market research companies like Forrester implemented long time ago a strategy to offer reports on main page according to your industry or keywords interests.

With a high chance, the website owner identified you as a company related to recruitment and change the page accordingly. A few exciting products on the market make this workflow easy to set up and execute.

However, how to understand who you are and what to present on the webpage? Leverage Intent data to push buying decision!

While IP reveals technologies are getting better and better in understanding what company we represent (think about Albacross / Leadfeeder / Clearbit), it is still a lot of room for improvement. Work-from-home hasn't created a positive impact on the quality of this data. The same goes for firmographics. Even if MarTech cookies identified your company, the quality of data still might be questions about the industry, company size, and category you operate in.

On the other hand, 1st and 3rd party intent data about your content consumption and engagement can deliver additional data points to structure the page and CTAs according to your interests.

Imagine, your intent-based marketing data provider has a direct collaboration with LinkedIn. It created algorithms to categorize LinkedIn content and create a unique profile of your interests based on your engagement with these posts.

Once the prospect lands on your home page, it became structured accordingly to his overall business interests. Marketing leaders focusing on inbound will see messaging related to response speed, real-time scoring, and retargeting. Outbound sales teams will get call-to-action to know better their network and clients' needs on the market.

Each will get peace of content relevant, personalized, and at the right timing to them.

That what we believe in here at Rocks & Gold, and happy to share with you our vision of B2B engagement.