A Note from Our Founders to the Infer Community
Our goal back when we founded Infer was to figure out how we could use predictive technology to unlock value for B2B companies. From the very beginning we were fortunate to sign-up amazing customers who have pushed the product, achieved significant lift, and inspired others to follow in their footsteps. With your help we’ve grown the Infer community 150% Q/Q and added best-of-breed companies such as AdRoll, Cloudera, New Relic, Optimizely, Zenefits and many others.
With this recent round of funding we’re excited to extend our lead in the B2B predictive space and release a wave of new product innovation. We’re going to be hiring across the board, but especially world-class engineering talent. We want to push our data science advances even further with new models and built upon the great use cases our customers have uncovered already, i.e. optimizing marketing campaigns, improving outbound sales, designing SLAs and shaping strategic planning. It is fun to re-imagine how companies should operate based on data!
Thank you again and here’s to an exciting, prosperous 2015!
Frequently Asked Questions
Why did Redpoint bet big on Infer?
Redpoint partner Satish Dharmaraj led our $10 million Series A round and stepped up again by investing an additional $25M in this Series B funding. This is somewhat unusual in venture investing. Hear from Satish on why this was a special case and what he sees in Infer. Read More
How does Infer plan on using the $25M?
Through our Series A round, we’ve been very capital efficient and focused on nailing repeatability. We’ve shown that with an A+ caliber team you can do a lot with a little, and we’re ready now to really accelerate growth. With our Series B funding, we’re going to hire aggressively across all functions, increase our sales and marketing efforts, and expand to several new industries and geographies. If you’re interested in careers at Infer, click here.
Did Infer consider outside investors?
Given our great growth and leadership in the market, we were very fortunate to receive considerable VC interest from both outside and inside investors. We considered our options closely, but in Satish we have a partner we really trust, so we’re excited to further align with him on our vision of bringing predictive to thousands of companies.
What kind of team has Infer assembled?
Infer’s leadership team is stacked with impressive talent, like our CRO Jim Herbold, who ran sales at Box for seven years, and former Salesforce VP and eleven-year veteran, Jamie Grenney. In addition, founders Vik, Chung and Yang have attracted an A+ engineering and product team that’s second to none, and they’re building models that consistently outperform Infer’s competition time and time again.
What’s an example of a company using Infer?
Payscale is one great example. Infer helps them focus their sales teams on deals most likely to close. In 6 months since implementing Infer, they’ve been able to send sales 22% fewer leads but close 14% more. It has also given them a more objective way to evaluate the effectiveness of their marketing programs. For more on Infer’s incredible customer community, click here.
What are some of Infer’s latest product advances?
Recently we’ve made tremendous advances in our behavioral models that predict how likely a prospect is to make a purchase in the next fourteen days. In addition, we’ve extended our platform beyond filtering and prioritizing leads to far-reaching predictive applications for sales and marketing like optimizing marketing campaigns, improving outbound sales, creating intelligent lead routing, designing sales service level agreements, and shaping strategic planning.
What types of career opportunities are there at Infer?
With today’s financing, Infer will be aggressively ramping up hiring across all functions. Feel free to check out our current job openings here.
How can my company get started with Infer?
If you’re interested in using Infer at your company, contact us to get started. We’d be happy to answer any questions you have and build a no-risk personalized model.