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Retail Analytica

A Hybrid Self-Adjusting Customer Interaction Assessment Tool

Kazakhstan, Almaty
Market: Artificial Intelligence
Stage of the project: Idea or something is already done

Date of last change: 15.11.2020
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Idea

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).

Current Status

400 000 USD revenue with 2 large FMCG in 30 months

Market

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).

Problem or Opportunity

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.

Solution (product or service)

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.

Competitors

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.

Advantages or differentiators

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.

Finance

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

Business model

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

Money will be spent on

Product technical boost

Offer for investor

250K for 15% equity

Team or Management

Risks

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

Incubation/Acceleration programs accomplishment

A Quest Ventures portfolio company (50K USD raised)

Invention/Patent

Smart Shelves - but this is a different product
For smart retail audition we have filed an IP application
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Idea
Current Status
Market
Problem or Opportunity
Solution (product or service)
Competitors
Advantages or differentiators
Finance
Invested in previous rounds, $
Business model
Money will be spent on
Offer for investor
Team or Management
Mentors & Advisors
Lead investor
Risks
Incubation/Acceleration programs accomplishment
Won the competition and other awards
Invention/Patent
Photos
Product Video