Netflix, which has developed a radio-powered tagging system and corresponding data platform to read and parse information related to those tagged items, has raised $67 million in a Series C round of funding, bringing its total funding to $100 million. The money will be used for both R&D and rolling out services to its first customers.
“We solve our customer’s biggest pain point, which is a lack of real-time data in physical stores,” Anat Shakedd, the CEO who co-founded the Tel Aviv-based company with her husband Lior, said in an interview. She describes Netfix’s solution as the “only tech in the market” that doesn’t require a battery to be able to transmit substantial data at a long range.
This latest tranche of money has been co-led by Pitango Growth and Saban Ventures, with previous backers Battery Ventures, Intel Capital, Pitango First and Vertex Ventures also participating. Prior to this Series C, Netflix has been relatively under the radar while working on its technology and deals with its first customers.
Pitango Growth and Saban Ventures led the current round of funding, with existing backers Battery Ventures, Intel Capital, Pitango First, and Vertex Ventures also participating. Netflix has been relatively under the radar while developing its technology and dealing with its first clients before to this Series C.
Netflix’s valuation was slightly over $340 million before this round was fully concluded and merely $53 million, according to PitchBook. With the Series C funding at $67 million, the startup’s post-money valuation would be little under $356 million.
She added that Netflix has further signed agreements with “four of the largest retailers in the world” — no names disclosed — that are in different phases of development, and is having discussions with 20 other large retailers.
Physical retailers today operate in a data desert — they set out items and sell them, hoping for success, and often have large amounts of stock that don’t sell; it’s a lot of trial and error with a few bits of observation and historical data thrown in to understand why — but by being physical locations, they are essentially sitting on a mother lode of useful data if they can tap into it better.