Motif Analytics Inc., the developer of a data exploration platform powered by artificial intelligence, today announced that it has raised a $5.7 million seed round led by Felicis and Amplify Partners.

The raise also included the participation of angel investor group InvestInData. The consortium includes more than 50 engineering executives from Netflix Inc., DoorDash Inc. and other major tech firms

Studying the sequence of events that lead up to a purchase can help companies identify new sales opportunities. An online retailer, for example, may determine that two thirds of the shoppers who buy a certain product previously clicked a banner ad created to promote the product in question. In response to such information, the marketing team could boost its banner ad budget to drive more purchases.

In practice, the sequence of events that precedes a sale is often much more complicated. A user may make upwards of a dozen actions, such as reading product reviews and checking competitors, before making a purchase. Collecting accurate data about each step, preparing it for processing and then analyzing it can be technically challenging.

San Francisco-based Motif has developed a platform specifically optimized for studying multistep user journeys. According to the company, the platform is easier to use than more general-purpose analytics tools that are mainly geared towards other types of data science projects. Motif claims mapping out what actions users take before a purchase can take days or weeks with such tools.

“I haven’t met a head of growth or operations who was happy about their team’s ability to use company data in everyday decision-making,” said Motif co-founder and Chief Executive Officer Misha Panko. “They try and get disillusioned with self-serve analytics tools, which promise one-click solutions and trivialize the complexity of cleaning, modeling and interpreting data.”

Motif’s platform features an internally-developed query language dubbed SOL. It’s positioned as a simpler alternative to SQL, the syntax used by most competing analytics tools. Motif Analytics claims SOL makes it possible to implement most “practical” queries in under ten lines of code.

The platform runs SOL code using a query engine that the company has likewise developed in-house. According to Motif Analytics, the engine makes it possible to customize the precision with which the results of an analysis are generated. Users working on data science projects that require only limited precision can trade off some accuracy of increased query performance.

By default, the platform runs analyses in the cloud. Data science teams working with sensitive records can optionally process them locally using a feature called Local Mode. The feature is powered by WebAssembly, an open-source technology included in Chrome and other popular browsers.

According to Motif, companies can leverage its platform to map out the most common user journey that shoppers take before making a purchase. Moreover, the platform uses AI to identify the individual actions that make up a user journey and quantify their impact on sales. It can, for example, determine if users who redeem a coupon code may be more likely to complete a purchase than those who don’t.

The company announced its seed funding round today in conjunction with its platform’s launch into general availability. The new capital will help Motif accelerate product development efforts. According to TechCrunch, the company plans to develop a drag-and-drop interface that will remove the need for users to write queries manually.

Image: Motif Analytics