Account-based marketing: How to sweat third party data for intent insights

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Marketers will see a collapse of faith in third party intent data, as they quickly appreciate its limitations; however, there are ways to unlock its value and gain more nuanced and reliable insight into the 'who', 'what', and 'why' of intent data.

If marketers fail to capitalise on the explosion of interest in account-based marketing (ABM) this year, perhaps the most likely reason is that they will misunderstand the purpose of insight.

It’s obvious that understanding an organisation is one of the most effective way of targeting them with timely, personalised and engaging messages that turn interest into action. Intent data – both in-house first party data from martech & CRM systems, and third party information from publishers and social networks – can bring tremendous benefits to ABM campaigns, which rely on an deep understanding of an organisation’s motivations.

Unfortunately, publishers and ad agencies are often guilty of over-hyping intent data’s ability to provide us with this insight. Instead of giving marketers the key to understanding the B2B customer journey, they can make wildly optimistic promises based on weak evidence.

We hope that 2018 will be the year when brands learn how to treat intent data objectively, and build an approach that combines first and third party information to build a meaningful view of where accounts are.

What is third party data?

The first step in learning to harness the power of intent data is to establish what we mean by first and third party information.

First party data consists of an organisation’s own internal information, drawn from CRM systems or data management platforms (DMPs), inbound traffic to websites and social channels, or any other data gathered and held by an organisation. There are obvious advantages to first party data, such as the fact that hosted information is directly aligned to an organisation’s products and services, and is therefore a strong predictor of interest and intent.

But first party data has its limitations: volumes are likely to be low compared to external sources; more importantly, it can provide a skewed sense of customers’ intent. Brands gather first party data whenever a customer engages with their content – for example, by visiting their website or downloading a piece of whitepaper. As a result, first party data is always based on the brand’s context, and gives little insight into the customer’s specific needs.

First party data has its limitations: volumes are likely to be low compared to external sources; more importantly, it can provide a skewed sense of customers’ intent.

That is why brands need external data: to fill in the blanks and provide the context for customers’ intent.

Third party data comprises behavioural signals gathered from across the web’s publisher sites and social networks. Activities such as browsing, downloads, video streaming and search queries all help to fill in the blanks that enable brands to understand the “why” of the purchasing decision, rather than the “what” which is often all that first party data can provide.

What are the problems with third party data?

The great advantage of third party data is that prospective purchasers are more likely to seek out information from independent sources such as an online publication before browsing a vendor website. As a result, organisations that can harness this data will get much deeper insight into the buyer’s interest, much earlier and closer to the top of the sales funnel.

Knowing the value that it can bring to brands – not to mention the fact that it is fast becoming an important revenue stream for publishers themselves – owners of third party data are naturally keen to promote it as the silver bullet for almost every type of marketing campaign.

The problem is that there are still many questions surrounding the value and validity of third party B2B intent data, and often it is a blunt tool for highly-targeted activities such as ABM that requires a deep and accurate understanding of prospects and their intentions.

For example, there is currently no standard way of evaluating intent data, which can sometimes be little more than a list of IP addresses matched to a score against keywords behind the content the user has accessed. What’s more, the law forbids a publisher from revealing who has read an article, watched a video or downloaded a whitepaper, while some data sets may end up being too small to be of any real value once organisation and topic classification are cross-referenced.

None of these drawbacks should in any way discredit information from third parties, which still provide a trove of invaluable information to add to the “data mix” on which campaigns are built. Unfortunately, that’s not how it’s being sold to brands. It’s time that marketers got wise to third party data’s role in the marketing mix, and learned how to apply it most effectively.

How can you apply intent data to ABM campaigns?

The key to understanding intent data is to appreciate that there are almost limitless ways to get a view of a customer’s mindset. Account-based marketers will consider a huge range of data, from first party indications such as websites, to information provided by third parties such as content downloads, all the way through to primary research and existing relationships.

All this data is grist to the marketer’s mill, helping inform every part of the ABM process from account selection to planning and insight, through to messaging development, content and execution. Intent data is useful at every stage of the process, but is particularly valuable in enabling marketers to monitor hundreds instead of a handful of accounts, and wait for that spike of interest that indicates that someone will be particularly receptive to receiving tailored, targeted communications.

The key to understanding intent data is to appreciate that there are almost limitless ways to get a view of a customer’s mindset.

Take the example of an organisation selling to businesses in the oil and gas sector, where research has shown that there’s a broad, cross-industry interest in digital transformation. By layering intent data with other sources of insight, sales and marketing teams can identify where and when an account expresses specific interest in digital transformation, and react accordingly.

The initial ‘spark’ may be a piece of content downloaded from a third party website, or it might be a senior executive delivering a keynote presentation; the point is that a comprehensive ABM process will analyse a wide range of data from multiple sources to inform which tactical or strategic actions to take.

Know the score

With so much data to choose from, the challenge for marketers is how to give due weight to each piece of information. This is why third party data 'spikes' such as a whitepaper download should be scored or 'weighted' with other factors that are meaningful to the brand’s sales strategy.

For example, you may decide that multiple intent spikes across a series of related topics is more significant, or that intent is more meaningful if you have an existing connection with the organisation (for example, through social media relationships).

Scoring intent is fundamental to achieving great results with third party data. When it’s done well, it can bring quite mind-blowing return on investment, as software giant Oracle found when it used data to fine-tune its account selection process.

By applying the principles of intent data that we’ve outlined above, Oracle has been able to identify account opportunities before the customer has expressed official interest. As a direct result, the company shortened its pipeline by an average of four months, identified over 200 transformational opportunities and significantly increased its win rate.

These are results that third party providers simply can’t (and certainly shouldn’t) promise for their data; yet the information they provide is a crucial ingredient in delivering these outcomes. So, while marketers should be sceptical about third parties that overhype the intrinsic value of their data, they should seize every opportunity to add to their knowledge of their target accounts, and so start to anticipate customers’ needs – even before they know it themselves.

About Alisha Lyndon


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