Solution Provider Spotlight: causaLens

May 15, 2023
by Jerry Stephens, SVP and General Manager

Tenure With Current Company: 1 year
Years of Industry Experience: 20+ years

Give us a brief history of your company, when and how did you get started and what is your high-level mission statement?

CausaLens was born in 2017 by Max Sipos and Darko Matovski who both began their careers in finance.  Both felt that an opportunity existed in the world to create a technology which could enable humans to better understand cause and effect, a way to help humans better understand the impact as the world changes.  In January of 2022, causaLens raised a Series A led by Dorilton and Molten Ventures.

What would you like CMA and SIMA members to know about your brand/company?

We see an opportunity in the marketplace to enable organizations to understand causa and effect in a scalable way.  As the growth in interest in causal ai continues to grow exponentially, causaLens continues to be identified as the ‘trailblazer’ in causal ai which has been identified by Gartner on the Emerging Technology Hype Cycle.  We deliver an end to end platform, from data to decision with a focus on augmenting value with faster and better decisions.

What are some common questions you hear from current and potential customers, and how do you answer it?

Probably the most common question that I hear is ‘where do we start’?  What we have found is that most organizations have started to create strategies where causal understanding is at least integrated into an insights go to market capability.  We start with a single use case, related to a business opportunity and but causal in nature.  Very quickly, given the causaLens capability, we can demonstrate the capabilities of the platform and deliver a POC, connecting output and recommendations to decisions.

Any white space in the industry or areas you are looking to expand into?

Generally, causal ai is new technology so as we continue to work with some of the world’s leading companies, the white space is naturally into connected use cases.  We have built multiple use cases across both the demand creation and supply chain functional areas and delivery across both are resonating with clients and delivering material value.

What is the most important thing that needs to be addressed in the category management and shopper insights disciplines going forward?

I am not sure I know the ‘most important’ thing.  The way that I would answer this question begins with a reference to why I joined causaLens in the first place.  The two areas of focus which are critical for adoption of category management and shopper insights outputs are explainability and applicability.  I joined causaLens because I believe that causal ai enables organizations, at scale, to connect data science and analytics because it delivers explainable causal structural models and enable business decisions through counterfactual analysis, recourse, and the ability to build scenarios leveraging any number of variables.  In my opinion, this enables a far more operational capability versus scorecarding, augmented analytics, or traditional machine learning.

How are you thinking about the next 3-5 years in retail?

I can start the answer to this question with a strategy that won’t change for retail, increasing the organizational capability for customer centricity.  In terms of demand creation, I believe that the major shift for organizations will be their ability to integrate a robust understanding of investment impact and leverage this understanding for real time interventions and better predictive capability.