Motif Analytics Inc., a developer of an artificial intelligence-powered data exploration platform, today announced that announced Announced that it has raised $5.7 million in a seed round led by Felicis and Amplify Partners.
The funding also includes participation from angel investor group InvestInData.The consortium includes more than 50 of his engineering executives from Netflix Inc., DoorDash Inc., and other major technology companies.
Studying the sequence of events that lead to a purchase can help companies identify new sales opportunities. For example, an online retailer may determine that two-thirds of its shoppers who purchase a particular product have previously clicked on a banner ad created to promote the product in question. Depending on this information, your marketing team can increase your banner ad budget to drive more purchases.
In reality, the sequence of events preceding a sale is often even more complex. Users may take more than a dozen actions before making a purchase, such as reading product reviews or checking out competitors. Gathering 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 multi-stage user journeys. The company says the platform is easier to use than general-purpose analysis tools primarily aimed at other types of data science projects. Motif claims that such tools can take users days or weeks to plan what actions they will take before making a purchase.
Misha Panko, co-founder and chief executive officer of Motif, said, “I have never met a growth or operations leader who is so happy that their team can leverage enterprise data for day-to-day decision-making.'' ” he said. “They try and become disillusioned with self-service analytics tools that promise one-click solutions and simplify the complexity of data cleaning, modeling, and interpretation.”
Motif's platform features an internally developed query language called SOL. It is positioned as a simpler alternative to SQL, the syntax used by most competing analysis tools. Motif Analytics claims that using SOL, most “practical” queries can be implemented in less than 10 lines of code.
The platform uses a query engine that the company also developed in-house to run SOL code. According to Motif Analytics, this engine allows you to customize the accuracy of the analysis results produced. Users working on data science projects that require only limited precision can trade off improved query performance for some precision.
By default, the platform performs analysis in the cloud. Data science teams working with sensitive records can optionally process sensitive records locally using a feature called local mode. This feature leverages his WebAssembly, an open source technology included in Chrome and other popular browsers.
According to Motif, businesses can leverage its platform to plan the most common user journeys that shoppers take before making a purchase. Additionally, the platform uses AI to identify the individual actions that make up the user journey and quantify their impact on sales. For example, you can determine whether users who redeem a coupon code are more likely to complete a purchase than those who don't.
The company today announced a seed funding round in conjunction with the platform's general availability. The new funding will help accelerate Motif's product development efforts.according to tech crunchThe company plans to develop a drag-and-drop interface that will eliminate the need for users to write queries manually.
Image: Motif analysis
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