Intent data provides an exciting new frontier for marketers to develop better messaging, tactics, and strategies. Capturing and analysing intent data allows you to connect with buyers in a more relevant and meaningful way. Through it you can orchestrate demand in a manner that improves engagement, shorten sales cycles and accelerates deals.
Andrew Davies co-founder and CMO of demand orchestration platform Idio, walks us through the opportunities of intent data. You can pop by to say hello to Andrew at the Tech Playground area of B2B Marketing’s Ignite 2018 conference tomorrow, where exhibitors will be demonstrating the latest and greatest martech offerings.
What is intent data?
“Intent data” is exactly what it sounds like: data that reveals a buyer’s (or group of buyers’) intent to do something. Within the world of B2B, intent data shows what a buyer is interested in and, therefore, likely to buy.
Intent data can be implicit (i.e. inferred from the behaviour of a buyer) or, it can be explicit (i.e. declared by the buyer). It can be first party (i.e. generated from buyer activity on owned sites) or third party (i.e. bought from vendors that collect intent data from buyer activity on publisher sites).
Why is intent data so useful?
B2B marketers are already swimming in data. From contact details to firmographic insights and from past contracts to lead engagement scores, marketers can draw on myriad data points about their buyers and where they are in the sales cycle. The problem is that these same data points are often out-of-date as quickly as they are captured in a CRM or marketing automation tool.
At Idio, we often speak about how marketers are constantly driving forwards by looking in their rear-view mirror, i.e. using historic data that’s [perhaps] three months old in its relevance, when they should be looking ahead at what their prospects and customers might or are highly likely to do right now. This is why intent data is so useful – the predictive aspect: B2B organisations may not only possess a buyer’s firmographic details but also identify when they when they are in active and engaged demand stages.
How is intent data generated?
Buyers are actively researching your products and services, giving a signal of when and what they want to hear from you. This research can be done on your organisation’s own web properties – through reading your blog, downloading whitepapers, viewing product factsheets or visiting key web pages – or on third-party publisher sites with content that is relevant to your products and services. As each buyer engages with your blog posts, whitepapers, product pages, email programmes and social media, these content engagements reveal readers interests and predict what they’re likely to purchase.
Third party intent data providers collect these signals in partnership with content-rich business media sites. The data they capture is at an account level (e.g. Company ‘A’ is currently interested in these topics) and is good at identifying early interest, then powering account-based advertising initiatives. In contrast, first party intent data – a by virtue of it being derived from one-to-one interactions on your own site – is better applied for onsite personalisation and sales enablement. In the case of first-party intent data, gathered under your consent from your website permissions, you can identify both the account they are associated with and who they are as an individual within the account (e.g. Individual ‘P’ at Company ‘A ‘is currently interested in these topics right now).
In both cases, the method of generating intent data is the same: content is ‘tagged’ with metadata that describes the topics contained within it, buyer interactions with the content are tracked, and these interactions are used to build a data set of intent. The difference is whose content is used (third party media site or owned web property) and the granularity (typically, content on owned properties have a greater number of more descriptive topic tags, leading to a more accurate profile of intent).
How can my organisation unlock first party intent data?
First party intent data is becoming increasingly attractive for enterprise B2B organisations that want to create personalised buyer journeys but are hamstrung by large volumes of content and complex product portfolios.
To generate first-party data from your own content requires it to be tagged with metadata that describes the meaning of each piece of content. Topics can be people, product, places, organisations, and so on. For example, this article could be tagged with the metadata ‘Andrew Davies’ (person), ‘first party intent data’ (concept), ‘B2B Marketing Magazine’ (product) and ‘Idio’(company).
Of course, one article alone isn’t enough to build an accurate picture of you, the reader, but if we were to track your reading arc around B2B Marketing, we could build up an increasingly accurate picture of which topics are interesting to you and use that to identify your informational needs or purchase intent.
Once your content is tagged with consistent and descriptive topic metadata, the next step is knitting this together with your own buyer IDs (as stored in a CRM or marketing automation tool). In both cases, tagging and association with buyer profiles can be expedited by leaning on content intelligence solutions, if doing it manually is time or cost prohibitive.
How can first party intent data be used?
As with any new data set, the end goal is not simply insight but enabling B2B marketers (and marketing technology) to act on it to improve performance:
Optimise content marketing. By understanding your audience members’ intent as they engage with your content, you can identify the content topics driving the most buyer engagement and which topics are not resonating with the audience at all. Therefore, you can optimise your demand strategy to focus on the content topics your audience finds most interesting.
Insights for sales conversations. So, you’ve got a hot lead with a very high engagement score – what next? That score notifies you that the lead is engaged, but it doesn’t tell you what the lead is engaged about. Intent data helps you know what to talk about once you pick up the phone to a lead, improving the likelihood of a relevant and successful conversation.
Better segmentation. You might have segmented your database around job titles or industries. Both of these are quite crude buckets within which to parse your database. No two ‘Head of Digital’ is alike; they’re both humans with differing needs and interests. Segmenting by intent data (or combining it with your other data sets) means you can make your marketing messaging extra-relevant now that you know what content topic is going to be of most interest to that segment.
Optimise nurture programmes. Marketers are often guilty of creating nurture journeys for net new leads based on our own views of what they should read. This negates the buyers’ interests and intent, instead stereotyping them based on a data point, such as their job title or company. Demand orchestration technologies act on intent data to automatically change the nurture track a buyer is placed on, using intent signals from their own unique content consumption path. In short, your buyers now receive what they are interested in, not what you think they should be interested in.