Intent Data is starting to become the newest buzzword within the B2B marketing space. In the past few weeks, we attended three industry conferences for B2B marketers and had a lot of conversations with folks about data-driven marketing practices.
At this point, it’s clear that everybody wants intent data. Marketers get that intent data has practical applications ranging from identifying in-market buyers, lead scoring and nurturing campaigns to programmatic advertising, ABM and more.
The latest Demand Unit Waterfall has added two new stages – target demand and active demand – aimed at identifying target buyers before they have raised their hand or self-identified on your site.
According to SiriusDecisions’ recent blog post:
”third-party intent data can help determine which demand units not only are in ‘shopping’ mode, but also have experienced an identifiable event that means they could be in-market. This data then helps organizations determine where to aim their outbound marketing efforts.”
Yet, nobody seems sure about how reliable or valuable this intent data is, or what the differences are between offerings from various intent data providers in the market.
You might be wondering how reliable or valuable external intent data really is, and how to apply it in practice.
In other words, are these intent signals relevant? Are these intent signals predictive of purchase behavior?
What do we mean by predictive?
By using intent data to refine your lists and audience targets, and executing data-powered advertising and demand generation campaigns, are you able to see significant lift or increase in conversion rates, deal velocity, and pipeline creation?
In this post, we will offer some guidelines and provide our own data to help you evaluate intent data providers.
How relevant or reliable is external intent data?
For data to be used to pinpoint real purchase intent, you need to be confident that the data provider can accurately identify who is truly behind the activity.
The ability to accurately identify who is behind an activity depends on how the data provider is gathering that data and where the data is coming from.
In general, there’s two approaches to gathering intent data:
- Algorithmic / using web crawlers
- Human-volunteered, human verified
There are multiple places where intent data comes from. Places generally falls into two categories:
- Company websites, B2B publishers, business or technology focused online communities.
- Public data from social media networks, i.e. Twitter
At this point, a number of providers are crawling B2B-focused and general consumer websites for activities that are related to business solutions. These data providers are using methodologies that allow them to provide intent data at the account or company level.
Bombora, The Big Willow, 6Sense and MRP/Prelytix are a few companies that fall into this category.
How are these intent data providers differentiated?
Other providers (i.e. The Big Willow) leverage device tags (on PCs, tablets and phones) to track what devices are consuming content. The Big Willow associates the content with intent, and then associates the devices – as much as it can – to companies using reverse IP lookup for IP addresses registered directly to a specific business.
If the IP address belongs to a service provider like Verizon or Comcast, The Big Willow applies a proprietary method that finds the device location based on IP address and infers a match with businesses near that location. This method isn’t 100% reliable but can work if there is just one business in a particular industry near that location.
Using reverse IP lookup to identify “active” companies is not a perfect solution, because IP lookup can only resolve a fraction of IP addresses into accurate domain names, and even fewer outside of North America.
The reliability of the data also depends on what specific content the user has interacted with.
For data to be used to pinpoint purchase intent, you need to trust that the content used to produce the activity is actually related to your solution.
As TechTarget pointed out, it’s not enough for an algorithm to find content that matches your product category keyword – let’s say “Flash storage”.
For a niche topic such as “Flash Storage”, there simply isn’t that much highly focused, in-depth content across the entire web, and even less that shows up high enough on search engines to drive significant traffic volumes. As a result, intent data on product categories may not be all that useful.
While some general technology and consumer websites are now allowing data providers to scan their sites and aggregate the information, premium publishers do not allow their sites from being included in these scans. For example, Gartner is not letting third party data providers identify who is reading the latest Magic Quadrant for Business Intelligence and Analytics Platforms.
How do you want to utilize intent data?
One other important point of consideration is how you want to utilize this data. A list of active accounts without named contacts restricts data’ usefulness to marketing activities such as programmatic ad targeting. If you want deeper funnel applications, you need to get intent data at the individual user level.
At this point, companies like TechTarget and The Aberdeen Group have spent years producing in-depth content for serious technology buyers researching and making enterprise purchase decisions. They employ industry experts to provide high quality editorial content, and has built up databases of opt-in users who have explicitly said that they are looking to make purchases in certain technology categories in a given timeframe.
Business-focused video destinations like BrightTalk are known for their webinars on topics like Marketing, Sales, Finance and IT its site, and can provide you with a list of leads who have viewed 3rd party content in your space (i.e. based on keywords webinars are tagged with).
Software review sites like G2Crowd and Capterra can show you who is reading reviews in a given product sub-category.
Because the content produced by these B2B tech media companies is more in-depth and relevant to specific search queries, these sites are deemed more relevant by Google and tend rank much higher in Google searches.
For example, TechTarget has found that 90% of inbound buyer traffic to its network of 140 websites originates from very granular keyword searches and clicks on highly ranked content.
According to TechTarget’s whitepaper, “the pattern of web activity looks like a scatter grid in the enterprise buying space. For any given tech segment, there are tens of thousands or even millions of site visits every month. But activity coalesce around the most granular content that ranks the highest in search.”
As the whitepaper explains, “the strongest intent signals cluster at the intersection of relevancy and rank. So while there’s a lot of activity happening beyond that, the less specific the content, the lower it ranks, and the more dispersed the activity becomes”.
While user-level, user verified intent data may start to sound like the better option, there are limitations to consider. Given the focused nature of these third party B2B content communities, the number of contacts you can find showing interest in your product category for locations you care about may be more limited, and the cost of each intent-based contact will be higher.
Now, let’s consider social-media based intent data.
At this point, Socedo is the only company to provide individual contact level intent data for B2B companies from Twitter activities. We can tell you who is investigating or showing an interest in your product category or business space based on people’s real-time actions on Twitter.
For example, if you’re selling business intelligence software to enterprises using SQL Server, Socedo can tell you whom in your database is engaging with other BI/data visualization vendors, industry influencers and the handles of relevant professional groups in your space, as soon as these leads take relevant actions.
What sort of match rate will you get?
One thing to consider with any intent data provider is the match rate: the percentage of contacts in your database that can be matched to the intent data providers’ database.
Socedo has found that typically, 10 to 15% of leads in a customer’s database can be matched to their Twitter profiles.
The percent of socially engaged leads (to matched profiles) and the volume of social media activities vary based on how many keywords or keyword groups the customer tracks, the type of business the customer has, and the types of roles the customer is targeting.
For example, marketers and salespeople who work at tech companies tend to be highly active and engaged on Twitter, while finance managers in the manufacturing industry tend to be less active on Twitter.
Although this match rate might seem low, this number obscures some things.
Chances are, you have a lot of Data Deadweight, or prospects who do not open, click, respond or even opt-out of your marketing emails. You may have these too old contacts who don’t have any real interest in your technology because it’s gotten too easy to purchase new lists of leads. This is a common problem for our customers and our own marketing team.
What matters is identifying the prospects who have genuine interest in your solution space and are currently in a buying cycle. To understand how relevant social media signals really are, let’s take a look at some conversion data.
Conversion Data on Socially Engaged Leads
At this point, we’ve taken lead lists from multiple customers (typically with at least 10,000 leads each), added relevant social activities onto these lead records, and studied historical conversion rates for all leads on their lists.
In all cases, we found that socially engaged leads are more likely to convert compared to the baseline – all leads in an organization’s database.
We’ve also determined that the best time to reach out to someone is within the same day that they showed an interest in our solution space.
We’ve seen statistically significant lifts in email open rates and CTRs when we send someone an email at the “right time”, triggered by their social media actions, versus sending them cadenced nurture emails.
Conversion Rates for a Global Technology Company
One of our customers – one of the largest technology companies in the world – is looking to increase their Lead to MQL (Marketing Qualified Lead) rate for a couple of product lines in the U.S. and in Canada. They are tracking Twitter engagement around their own product lines, competitors, and hot topics in their space.
They found that leads who have engaged with their own Twitter handles are anywhere between 200% to 424% more likely to convert into MQLs compared to their baseline conversion rate.
This tech company also found that leads who have engaged with their competitors are about 100% more likely to convert to MQLs compared to their baseline.
When we looked at one segment (U.S. – based leads), we discovered that when leads engage with at least one of their tracked keywords two or more times, they are 100% more likely to convert compared to their baseline.
By lead scoring social actions that have higher conversion rates than their baseline, the company’s marketing team can pass additional MQLs to their sales team and increase their contribution to pipeline.
Data Provider on M&A, PE and VC Transactions
One of our customers sells M&A, PE and VC transactions data to investors who want to keep pulse on their markets and make intelligent investment decisions.
This customer has found that leads who engaged with any of their tracked keywords are 29% more likely to convert compared to their baseline. Leads who talk about certain topics (i.e., blockchain, crowdfunding) and follow certain competitors (@cbinsights) are 50% to 200% more likely to convert compared to their baseline.
In this case, a conversion is someone getting a demo of their platform.
Data from Socedo’s Marketing Team
Socedo’s marketing team is a customer of Socedo’s data.
We found that nearly 25% of all leads in our marketing automation database have taken at least one relevant social action per month.
In the past 90 days, 24% of all Marketing Qualified Leads delivered to our SDRs came from real-time social media actions.
While these MQLs do not convert into Opportunity at as high of a rate as say, trial requests from organic search, they convert into Opportunity at the equal rate as leads consuming our content from our emails and our blog in the past 90-days.
In the month of May, leads from social actions converted into Opportunities at a higher rate than leads who clicked on our emails.
Because with we have contextual data on our leads, we are able to contact leads at the right time – as they are doing research in our space -and provide them content tailored to their interests.
To date, we’ve sent over 50,000 real-time, intent-based emails to over 20,000 leads. We’ve learned that the best time to reach out to someone is within the same day that they showed an interest in our space.
To make sure that our emails are engaging, we’ve segmented our leads into 20 topical tracks based on their interests.
For example, those who use the hashtag #contentmarketing and follow @CMIContent are put into the “content marketing” track and receive an email pointing to a blog on content marketing best practices as soon as they engage with one of the keywords in that group.
We found that on average, these real-time emails average about 40% open rate and a 3-5% click through rate.
Those rates are more than double that of our typical role-based nurture emails. These rates have stayed consistent in the last eight or nine months that we’ve been running these real-time email nurtures.
If you’re looking to leverage third party intent data to fuel your demand generation programs, be sure to ask the right questions to understand exactly what each data vendor can provide.
We recommend you ask the following questions to assess their capabilities:
- What data sources do you provide? What websites/online communities/social networks are you getting this data from?
- Are you providing account/company level data or individual contact level data?
- Has this data been verified by humans (i.e. phone calls)?
- How granular is the data? Can you provide me data on specific actions people have taken (i.e. an entire Tweet, verified intent to purchase CRM in next 12 months) or do you just provide data at the topics/category level?
- Do you have your own technology to collect the data or do you license your data from other providers? What’s your specific data gathering methodology (i.e. website crawlers/scrapers, cookies, device tags, reverse IP address lookup, user volunteered data, API access from public sources like Twitter).
- What is your data match rate? What percentage of contacts in a typical CRM or Marketing automation database can be matched back to the data providers’ database?
- How often do you update or refresh this data?
- What format does the data come in? Can I consume it through direct integration with my marketing automation or CRM system? Is it available through an API?
- Can I use this data to automatically trigger workflows? For example, can I use this data to put contacts/leads into different email tracks, for programmatic advertising, or use this data in my lead scoring system?
If you’re interested in seeing whether social media-based intent data can make a difference for your business, contact us and we can set up a free trial and proof of concept. As a proof of concept, we will:
- Help you decide the right keywords or signals to track
- Provide you with the data match rate and activity volume for leads in your database
- Add historical engagements onto lead records for existing leads
- Run an analysis to understand conversion rates and likelihood to convert for leads that engaged with each keyword.
- Help you figure out how you can leverage our data, whether it’s through lead scoring, to provide insights for your sales team, or to run intent-based marketing campaigns.