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The Buyer’s Journey Report

Visualizing the Buyer’s Journey with Intent

How buyers buy and what you can do to be top of mind

Much of the buyer’s journey happens behind closed doors. So how do you find the buying behaviours that are traceable, and make them work in your favour?

Intent can’t tell you everything, but layering buying behaviours, from multiple sources, lets you know when someone’s in-market, how close they are to buying, and how you can make sure you’re top of mind while they’re looking. To test this theory, we mapped the buyer’s journey. Here’s how:

Using technographics, we found any company that installed HubSpot, Stripe, or Shopify, over a 90-day period. From there, we analyzed nearly 1,000 companies to find the relevant intent signals each company showed in the 90-days leading up to installation. Those intent signals include engaging with competitors, custom keywords, hiring relevant roles, or attending events. From there, we used the timeline from first sign of intent to install and the different intent signal types to visualize the buying process.

How does buying intent change from beginning to end? How does what you’re selling impact buying behaviour? Are competitive signals further in the buyer’s journey? And what can marketers do to turn data like this into a competitive advantage?

On that note, we broke the buyer’s journey into 4 stages. Each stage makes up 25% of the buying cycles. In other words, if the buyer’s journey that’s visible with intent is 100 days, Stage 1 is days 1-25, Stage 2 is 25-50, and so on. 

The Buyer’s Journey as Seen by Intent

Across nearly 1,000 companies a few trends were universal:

    • Action-based intent increases 60% from Stage 1 to 2, 36% from stage 2 to 3, then drops heavily in the final stage of buying.
    • Competitive engagements peak approximately 80% of the way through the buying cycle.
    • Most signals peak then fall, except competitive signals which continuously grow.
    • Hiring is prioritized about 60% of the way through the buying cycle.

Key Findings and What to Do About Them

52% Drop in Stage 4 But Competitive Signals Grow

Third-party intent across the public web drops by 52% in the final stage of the buying cycle. But competitive signals are stronger than ever.

Why? Enter the Dark Funnel.

By now, buyers have narrowed down their picks. Instead of hiring, reading content, or interacting on social, they’re likely in meetings with vendors, chatting with colleagues, and getting approval internally.

What to do with this data:

    • If a buyer’s been showing intent for a while, focus on more direct channels like hyper-targeted ads and outbound sales.
    • Prioritize competitive and value-based messaging with social proof and comparison charts.
    • Pay closer attention to first-party channels if third-party signals decrease to check if buyer’s are still looking.

Why Stripe Has 4x the Competitive Engagement

Buyers looking for Stripe engage with competitors 4x more than buyers looking for HubSpot. There are a few potential reasons:

  • Decision-makers for HubSpot have likely used it, or a competitor before, and have a preferred brand. Even if they do research, there are two prominent brands in the space.
  • There’s less commitment involved when evaluating Stripe or similar compared to a CRM. If one doesn’t work out, it’s easier to switch or take the trade-off of less functionality for a lower price compared to a bad CRM choice that could lead to months of work.

What to do with this data:

    • Use product-led marketing to help buyers visualize their workflow in your tech before buying, helping you stand out and set expectations for once they’re set up.
    • Complex implementation and competing with big brands like HubSpot? Focus messaging on features you have that they don’t. Use intent signals to see what your buyers care about specifically and let that shine.

32 Intent Actions Before Buying

Keep in mind, this number varies depending on your market. HubSpot had more signals than Stripe for example. And it’s based on third-party intent across the public web.

Combining this with sources like first-party intent, or review site data, you’ll get even more visibility. However, that doesn’t mean these numbers can’t play a role in your strategy.

  • 24/32 are custom keyword engagements
  • 4/32 are competitive engagements
  • 3/32 are hiring signals
  • 1/32 are event attendances

What to do with this data:

    • Create marketing automation to engage warm accounts as they start showing intent. If you have the granularity to see the types of intent evolve, tailor your messaging to what buyers specifically engage with.
    • Automate the creation of ad audiences so as soon as buyers enter the market, they start seeing your name pop up. Use targeted search ads to be first on the list as they do research.
    • Build intent into your lead scoring model to pass leads to sales as they are warmed up between engaging with other content and competitors, and starting to see your ads in their feeds.

46% of Hiring Happens in the Third Stage of Buying

Hiring plays an important role in buyer intent. Companies spending the resources to grow a team, often need new tech to to set them up for success. Whether new teammates have tools they love from a previous job, or a brand new team is being built, tech installs are almost inevitable.

If a company is hiring a bunch of SDRs, they likely need sales engagement tools. If they’re building out a content team, they might need to add or update their CMS. The trick is catching this and getting there first.

What to do with this data:

    • Create hiring-based content. An onboarding checklist, guides to setting and tracking goals, a compiled list of relevant people to follow on LinkedIn. These build awareness, get your name circulated internally, and place you top of mind once they’ve hired.
    • Monitor when fit companies are hiring for relevant roles. Factor this into lead scoring, use it as personalization, and even create marketing drip campaigns tailored to companies actively hiring.

What Else?

Shedding light on the dark funnel, finding the impact of brand and implementation risk on competition, and seeing the timeline of the ebbs and flows of buying behaviour are the shining stars of this data.

But, there are other stats that are either a) helpful, or b) just fun to know.

  • 910x hiring signals were shown for HubSpot vs other technologies
  • 951-200 employee companies are the bread and butter across techs making up 28% of all pre-install intent
  • 97% of installs happened on December 20th making it the biggest install day
  • 942 companies installed tech on December 25th

What Next?

Picture this: this type of data, only this time it’s about your prospects with the actions they’re taking and decisions they’re making in real-time.

If you knew their next step, could you get there before competitors?

Find some time with our team and get a sample report to see who’s looking.


About LeadSift

LeadSift, a Foundry company enables B2B tech companies to find, reach, and convert in-market decision-makers.

By layering intent signals mined from the public web, with research-based intent and proprietary tech, we deliver actionable and relevant leads. LeadSift was acquired by IDG (now Foundry) in December 2021.

Moving beyond targeting by static profile elements like title or company size, we show you who is engaging with competitors, custom keywords, events, technographics and topics that are relevant to your company from the most comprehensive intent data sources on the market. Leads are scored and sent directly into your favourite MarTech, so you always reach the warmest accounts first.