How B2B organisations can create first-party buyer intent data
Behind the concept of intent data is the understanding that buyers are actively researching products and services online, thereby giving a signal of when and what they want to hear from you.
As each buyer engages with blog posts, whitepapers, product pages, and social media these content interactions reveal their business needs and predict their intent. Consequently, buyer intent data is an increasingly popular dataset for B2B organisations that want to identify who is most likely to buy from them.
Third party intent data vendors capture buyer intent by partnering with B2B media sites and collecting audience content consumption behaviour (content downloads, video/streaming media, social interactions) on these sites.
Third party intent data collected from publishers typically relies on IP address rather than user registration, meaning it usually results in account-level insight (“An anonymous individual from Company A is interested in Topics B, D and Q”). This makes it useful for account-based advertising initiatives targeting prospective buyers who are currently offsite.
First party intent data can be generated by organisations that have large volumes of content and a high amount of onsite buyer interactions. Web visitors to an organisation’s website can be identified at an individual level (for example, if they relinquish a name and email ID in a lead capture form). Here you not only have an identified individual but also their unique business needs and likely intent – exactly the first party dataset required to power a relevant onsite experience with product, content or offer recommendations, and provide actionable insight for Sales and account management.
With that in mind – how can B2B businesses generate first party intent data?
1. Become a B2B “brand publisher”
B2B organisations that want to generate their own first party buyer intent data need to have (or start producing) large volumes of content. Intent is captured from buyer research and in a complex, prolonged sales cycles, content is the vehicle through expertise and credibility is built, relationships are nurtured, and buyer research is done. This is particularly the case for asset management firms, information services companies and technology businesses with myriad product offerings and buyer personas.
Becoming a brand publisher required businesses to move from a product-focus to a content focus, providing content that is informational and meets buyer needs. Barclaycard Business Solutions is a notable example of a B2B business that has become a “brand publisher” and are publishing on a wide breadth of topics for their business audience.
2. Add weighted topic-level metadata to your content
After creating a large corpus of business content, the next step is categorising it and making it machine-readable.
Use descriptive metadata to tag your content makes it easily searchable. Metadata can go well beyond typical tags such as ‘content type’, ‘date created’ and ‘author name’ – and extend to the topics contained within the content. These might include people, places, products, events and technical terms.
Tagging content with metadata makes it useful for systems (and humans) to understand what it is about – the more granular and exhaustive the better it is. More advanced with content analytics tools can go beyond simply identifying topics in content to ascribing weighting to it each topic: thereby identifying how important or how prominent a particular topic is in an article.
This ability to add topic weighting to a piece of content is critical to understanding the intent of a reader and calculating what exactly they are interested in.
3. Log the topic interactions in a CRM or MA tool
Modern marketing automation and CRM tools typically present the user with a clickstream of URLs that an individual has visited.
This manifests as a “lead score” – a cumulative number based on a buyer’s onsite behaviour as they visit key (scored) pages. The problem with a clickstream or a score is that whilst it legitimately identifies a buyer that is “warm” it doesn’t explain what they are looking for or why they are engaging with your web content.
However, when your content is tagged with weighted topic-level metadata, you can begin to identify the most common or most popular topics across a clickstream. Now, instead of a series of URLs or a high engagement figure, you can see the content topics that are recurring across those URLs which led to the high engagement score. You can now see the intent of a buyer on your site.
Logging this intent data in a CRM turns it into actionable insight for humans and knitting intent data to marketing automation IDs makes it an actionable dataset to improve onsite relevance and email personalisation.
It’s no longer enough to know that a lead is a good ‘fit’ or ‘highly engaged’ – high-performing organisations want to know if the lead is “in market”, and if so which product or service they are gravitating towards.
Whilst third party intent data is a boon for account-based advertising efforts, first party buyer intent data presents a clear advantage for those that want to improve the onsite customer experience with 1:1 email and web personalisation and optimised nurture programs.
Organisations such as Pure Storage have shown this. By delivering content relevance at scale, first party intent data powers better conversion rates, faster deal velocity and stronger alignment between marketing and sales. The path to this dataset is clear: publish content, tag it to make it machine readable, log content interactions in CRM and marketing automation tools, action it to improve B2B performance.