Foresight Works’ groundbreaking AI scheduling platform had the potential to revolutionize megaproject construction. But bringing this product to market had proven challenging for a number of reasons: the value proposition was complex, the target market was niche, and the competition was stiff — not to mention, they were already busy managing daily operations!
To break through, Foresight Works partnered with WEBITMD to launch a strategic go-to-market plan that would yield rapid results and scale over time.
We created an end-to-end growth strategy that would boost both marketing and sales performance for Foresight Works.
We ran an in-depth messaging and positioning workshop to build the foundation for Foresight Works’ growth. We defined their ICPs, buyer personas, competitive positioning, unique value proposition, brand voice, and more.
We set their sales team up for success with professional HubSpot onboarding and implementation. We also created a library of much-needed sales collateral such as vertical-specific product one-sheeters, a refreshed pitch deck, and follow-up sales sequences.
We developed a robust content marketing strategy that included eBooks, whitepapers, blogs, infographics, case studies, webinars, and more. We promoted this content through organic social media and monthly newsletters to establish thought leadership and build brand awareness.
To generate leads, we created multiple campaigns for paid social, including industry-specific display ads and LinkedIn document ads. This allowed us to craft specialized messaging for each buyer persona, which in turn maximized conversions.
Foresight Works has achieved tremendous results in less than 12 months of working with WEBITMD. Thanks to steady investment in content marketing and organic social media, traffic from organic search has increased by more than 4,000% and traffic from organic social has increased by 2,500%.
Foresight Works now has a growing pipeline of inbound leads each month, with the most recent quarter bringing in 28x more MQLs and 14x more SQLs than they originally hoped for.