In today’s accelerated world, the need for agile, affordable, and effective experimentation has never been greater.

Trial Run Eliminates The Obstacles Of Current Experimentation

Businesses face countless decisions to keep up with changing demands. You need to make investments wisely, but you’re often unsure if your ideas will drive profits or erode shareholder value. At the same time, successful experimentation can be both costly and time-consuming.

Generic placeholder thumbnailLack of standardized
protocols and workflow
Generic placeholder thumbnailFew analysts with
experimentation expertise
Generic placeholder thumbnailTime consuming to manually
collect and analyze data
Generic placeholder thumbnailExpensive high-priced

Trial Run was created to reduce the number of uninformed decisions businesses make – by redefining experimentation based on a superior service model and value-based pricing.

  • Simple

    Rapidly test and validate ideas to enable better decision-making

  • Scientific

    Forecast with greater confidence based on powerful synthetic-control algorithm

  • Scalable

    Conduct multiple trials and create a culture of experimentation

By combining advanced data science with a superior service model and value-based pricing, Trial Run lets your company create a true culture of experimentation.

Trial Run Supports The Entire Experimentation Lifecycle


  • Set business objectives & success criteria
  • Identify impact parameters
  • Identify optimal sample


  • Find counterfactual using synthetic control algorithm
  • Assess impact at granular level
  • Identify drivers of success/failure


  • Simulate large scale rollout and calculate ROI
  • Catalog learning for future use

By automating the experimentation lifecycle, Trial Run lets you focus on what’s important – making informed decisions based on the actionable insights delivered.

Featured Case Study – Store Remodeling

A leading US retailer sought to stay relevant by remodeling its stores but wanted to
accurately assess all the variables before committing to costs that ranged into the millions.

A US Retailer decided to conduct an experiment to determine the effect of in-store modifications on sales.

Space optimization Improved decor New motifs New fixtures New signage Remodeling downtime

Trial Run's unique algorithm simulated control parameters for each specific location to determine the store-by-store impact.

6% overall lift in Sales 22 (of 27) of the stores generated a positive lift 15%+ lift in few stores

Based on the results, the retailer decided to undergo remodeling of large stores only

Average breakeven of large stores was less than 2.5 years Average breakeven of small stores was expected to be 5-7 years

Trial Run lets you measure impact on sites as well as customers

Promotions Planning Store Remodeling Promotions Planning Digital Initiatives Product Cannibalization New Product Launch Marketing Campaigns Retail Operations New Services Shelf Optimization Distribution Strategies Packaging Redesign Loyalty Programs Merchandise Assortment Staff Incentive Plan Pricing Strategies

Key Features

    • Data-driven control store selection using proprietary synthetic control algorithm
    • Measure impact (Lift) at different levels of granularity
    • Calculate relative importance of store features in generating Lift
    • Remove time period with unusual activity during the analysis window
    • Flexibly to define sample size to detect a desired effect

Trial Run goes beyond the algorithm by providing you a superior service model and value-based pricing.

You can run your own experiments directly on the platform

or benefit from
the guidance of our Trial Run team

Trial Run Resource Center

We talk about business experimentation and analytics in the retail and consumer products space. Check out the links to our latest videos.