Blueshift raises $15 million from Softbank for its AI customer engagement tools
Four-year-old Blueshift, which describes itself as an AI-driven “customer data activation” company, has attracted backing from Japanese conglomerate Softbank. It today announced that it’s raised $15 million in series B funding led by Softbank Ventures Asia, Softbank’s AI-focused early stage fund, with participation from Storm Ventures and Nexus Venture Partners, bringing Blueshift‘s total raised to $30 million. It follows an $8 million series A raise in January 2016, and comes as former LendingTree VP of marketing Josh Francia joins the San Francisco-based startup as chief growth officer.
CEO and cofounder Vijay Chittoor said the funds will be used to accelerate product growth. “At Blueshift, our mission is to put AI in the hands of every marketer so they can transform their customer data into intelligent engagement on every channel,” he said. “With this latest round of financing … we are poised to accelerate our growth and deliver the power of AI to even more brands.”
The tech underlying Blueshift’s marketing platform — Interaction Graph — stores product and content interactions from customers of retail and ecommerce sites, digital media brands, consumer finance firms, and travel businesses. It’s continually enhanced with new attributes like channel engagement and affinity, Chittoor says, which are stored in a single index.
Above: Blueshift’s cloud dashboard.
Image Credit: Blueshift
In practice, Interaction Graph enables marketing managers to manage email, push notifications, text messages, social media accounts, and webpages in one place, and to A/B test and optimize content in an automated fashion. Through Blueshift’s Personalization Studio dashboard, admins can segment users in real time by behavior (i.e., attributes and time frame) and demographic (names and IP addresses), all while proprietary algorithms tabulate predictive scores to identify which users have a high or low likelihood of completing various actions. Moreover, the Interaction Graph computes those users’ affinity toward different product lines, categories, brands, authors, artists, and price points based on transactional data; highlights active and lapsing users; and optionally filters users by their responsiveness to various message types (by metrics or campaigns) and web traffic.
That’s not all Blueshift’s suite — which integrates with third-party platforms like Segment, SendGrid, Sparkpost, Branch, Facebook’s Custom Audiences, Enlighten, Demandware, and Twilio — can do. Its automated collaborative filtering feature crafts recommendations based on the behavior of customers who browsed or purchased similar items, and serves them through apps and websites. And its targeting tools allows managers to home in on segments of users, including those who abandon items and carts, with customized templates (built on Shopify’s open source Liquid language) featuring recent catalog updates, best-converting items, most-viewed items, best-selling items, and other types of trending content.
There’s merit to Blueshift’s approach. A recent report published by Forrester Research found that highly personalized, omnichannel marketing campaigns have the potential to generate four times more revenue and 18 times greater profits than static campaigns.
“Marketers need a system that was built ground up with AI,” said Storm Ventures managing director Tae Hea Nahm. “Savvy digital marketers are starting to realize that AI Marketing requires a fundamentally different architecture. Like the early transition to SaaS and now to AI, incumbents will have a very hard time re-architecting their platform.”
Blueshift’s current customers include companies like LendingTree, Vouchercloud, the BBC, Udacity, Zumper, The Muse, and Tradera.
Source: VentureBeat
