Retail Analytica

An automated hybrid customer interactions analyzer. This automated system learns from humans, whenever the comprehension level is below a certain value.

We have proven traction. The product has been raising sales of our key customers by 20%.

The system validates customer interactions, be it shop personnel persuading customers to buy a certain product, or promoters. The best scenario to increase sales is customer activation. By the way, 30% of promoters quit after the system starts listening and analyzing their activity (because promoters tend to cheat).

400 000 USD revenue with 2 large FMCG in 30 months

B2B

60M USD annually in Europe in a 2% pessimistic scenario. This is not hard to calculate, pending an average company check and a number of target businesses (from FMCG to banks and insurance).

Incremental Sales and Churn. On the one hand, due to improper instruction at the last mile in retail companies undersell. On the other hand customer churn also drops sales. So, on the one hand we allow to directly affect sales by monitoring bonus programs, on the other hand we allow improving retail interactions quality.

We analyze customer interactions and validate dialogues. Each company has its own goals and scenarios. Some companies follow interactions and their quality as well as related opportunities, others - hold bonus programs for sellers and need to validate each interaction and sale. Some companies use checklists, others -keywords or even transcribe with us and get analysis from us. The system is hybrid - it is a combination of humans and the machine / learning engine.

Verint, Speech Analytics -they are rathe partners, as they do not target retail - they produce tools to rather monitor calls, and even though they are able to become serious competitors if decide to target retail, we act in parallel, not similar markets. And we use this time to become as smart and as self-adjusting (AI-wise), as possible.

A hybrid listener in retail. Normally companies analyzing speech listen to call centers, PBX, SN. In our case we are targeting retail. The self-learning system is soon to learn to generate marketing reports independently. The self-learning system sends unclear pieces to humans, humans correct it and send it back to the system. The system learns and avoids people's help in the future. In noisy environments and in areas with multiple dialects an artificial intelligence is a must.

ACQ (customer acquisition cost)=1K USD
LTV (lifetime value per 1 customer)=100K USD

Freemium, PAYG (pay per contact). Could also be a one-time sale under license.

Product technical boost

250K for 15% equity

GDPR, but that is solvable by many tools similar to PCI DSS (masking, encryption, impersonalization).

A Quest Ventures portfolio company (50K USD raised)

Smart Shelves - but this is a different product
For smart retail audition we have filed an IP application