Contextual Technographics Add Depth and Actionable Insight to Sales and Marketing Data Stack
IntentData.io, Inc. announces the release of Contextual Technographic Data to fill a gap in enterprise and rapid growth companies’ marketing data stacks.
Technographics are commonly used as part of ICP (ideal customer profile) account identification and prioritization. Whether to identify opportunities to displace a vulnerable competitor, focus on prospects with unmet needs, perform broad market research, identify complementary products that integrate well, or any of a number of other applications, technographic data is used by marketers in many industries.
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It’s had a significant shortcoming, however, in the collection methods and missing context. Normally collected either from website tags (for marketing and sales tech primarily), notoriously inaccurate phone surveys, or modeling, technographic data collection has relied on methodologies that were limited in scope and prone to errors and inaccuracies.
Further, data was collected and reported as a static factor – in a binary yes/no way. That overlooks critical contextual insight that’s important for targeting and sales. Optimizing technographics for maximum marketing and sales value, in addition to propensity to buy modeling, requires overlaying technographic data on active intent engagements.
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IntentData.io’s Contextual Intent Data addresses both issues. It’s sourced both through the commonly used techniques of observing website tags and by crawling job descriptions to identify companies seeking expertise with specific software. Job descriptions have long been recognized by savvy competitive marketers as a source of deep and valuable insight into a companies operations.
“This really is a game-changer for the marketing data stack” says Ed Marsh, CRO of IntentData.io, Inc. “The real power in technographics comes via a combination of insights into what is – the current tech stack – and what’s likely to be – contact level™ intent data signals that overlap. That’s what we’re doing.”
Contextual technographic data is helpful not only for software companies, but also for service providers who support certain platforms and categories, and product manufacturers that interface with specific software.
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