Product

Setting up and running an online store has become incredibly simple, resulting in the significant expansion of the e-commerce market. Software players have rushed to act as the picks and shovels, however there remain untapped opportunities.

Pricing is a powerful lever for online stores, but the challenges of manual adjustments and optimisation hinder the process.

So what’s so difficult about it?

Existing software providers in the market mainly concentrate on basic rule-based optimisation or rely on traditional machine learning models. However, rule-based approaches mean businesses miss out on potential revenue, while traditional ML models lack accurate predictions due to limited training data and ability to attribute success to specific changes.

Revmass offers e-commerce stores automated price optimisation through a combination of traditional ML models and A/B testing.

Automated - Price changes and ML models are fully automated, streamlining the optimisation process

A/B Testing - Real-time data generated from A/B testing is used to enhance the performance of ML models and address data limitations

Attribution - Revmass isolates individual changes in A/B tests to accurately identify the factors driving an uplift in performance

Founders

Tommy Dai, Co-Founder & CEO - Previously investment director at Olsam and investment banking analyst at BofAML. BSc - Economics, University of Bath

Ben Marshall, Co-Founder & CTO - Previously data scientist at Waitrose and quantitative strategist at XAI Asset Management. MSc - Advanced Quantitative Methods, University of Bristol

Kieran Goodacre, Co-Founder & CPO - Previously head of product at Dazne and co-founder of ReferralHero (acquired).

Spotlight Analysis

Strengths

• Strong traction: baseline model has been proven in UK’s biggest omni-channel retailer, generating a 100% uplift

• Domain expertise: the team has significant experience working closely with pricing models and medium-sized e-commerce stores (target customer)

• Market conditions: e-commerce has been hit hard with rising costs and supply shocks so businesses will be more willing to take advantage of optimisation software

Weaknesses

• High churn: traditionally medium-sized businesses have high software churn with an average of 3% monthly

• Omni-channel integration: larger e-commerce stores will require integration across all their major customer touch-points

Market

Optimizely - Acquired by Insight Partners and Sugar Capital through a $1.16bn LBO in September 2018

Intelligems - Raised $4.2m seed round from Matchstick Ventures and Vinyl Capital in February 2023

Key Details

Year founded: 2023

Summary: Revmass offers e-commerce stores automated price optimisation through a combination of traditional ML models and A/B testing.

Raised to date: Bootstrapped

Business model: Monthly flat fee for smaller customers and revenue share on uplift for larger customers.

Currently raising: Yes, £750,000 with 50% committed by a lead VC

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