Random Walk’s technology driven data ensemble helps investors identify potential inflections before they are priced in. Utilizing a combination of several email and web consumer panels our systems identify and report changes in consumer preferences for key products and services.
With a robust international web panel our intelligence dissects organic online engagement trends for over 150 consumer brands.
For several hundred brands we are able to track new sign up related email confirmations.
Our team of data scientists provides the industry’s most robust analysis on timing and trend changes in promotions with history dating back more than 4 years.
Random Walk’s technology parses and categorizes millions of emails from over 150 brands to accurately quantify changes in promotional cadence and discounting, new customer acquisitions and purchasing habits.
Random Walk is a technology driven independent firm focused on quantifying changes in how large public brands are interacting with their leads and customers and then measuring the consumer’s response.
Our team of data scientists uses natural language processing in order to classify and categorize more than 100,000 digital messages from 200 brands weekly. This helps generate real-time insights into how organic demand for brands maybe changing.
Since inception in 2011, our insights have identified hundreds of significant inflections before operating results are made public. With our weekly updates we can capture changes in demand and sales trends in near-real time.
We uncover real-time inflections in demand. Our clients are alerted to these unforeseen changes in consumer trends and how they could impact growth trajectories.
Our proprietary email intelligence quantifies changes in how aggressive brands are in "pushing" offers to their current customers and lead base.
August 2019: Our proprietary categorization system altered investors that ULTA began sending a wide range of 25% off, $10 off and other promotions to different cohorts in the Summer of 2019. Soon after ULTA reported an-earnings miss and $100 share price decline.
Our systems help investors decipher whether increases in revenues are driven by increasing demand for produucts or just sharp discounts.
December 2016: In late 2016, several well-followed analysts, likely motivated by bullish credit card transactional data promoted JCP as retail turn around candidate. However, our email intelligence successfully identified explosive growth in email promotions. This helped alert investors that the increases in revenues the credit-card data was showing was not organic and instead a result of steep70-80% off sales.
Our proprietary real-time access to over a million unique anonymized email inboxes allows unparalleled insight into consumer adaption rates of novel products and services.
January 2019: Heading into 2019 our email intelligence alterted our investor partners to a sharp delcine in tne number of customers receiving "new account activation" related emails. Soon after EB reported worse than expects results slicing shares in half.
Our email intelligence helps investors understand how much "push" is rqeuired to create a sale
October 2017: While analysis and media were squaking about a potential GPRO turnaround surrounding the release of the HERO 6, our data indentified an all-time record volume of promotinal emails and sharp discounting of the HERO 5. The weakness in demand our systems identified foreshadowed tepid holiday sales and share prices collapsed nearly 50%.
Our web panel data ensemble goes far beyond generic mass disseminated web traffic. For nearly 100 brands, we are able to track activity to the actual checkout URL pages.
July 2019. Despite alot of enthusiam around AI, machine learning and "fashion tech" our analysis of online checkouts for recent IPO Farfetch indicated rapid slowing in consumer checkouts. After reporting rapidly decelerating sales, FTCH share prices dove more than 40%.
Our systems use robust real time data to detect when demand for key products and services could be changing
Changes in Promotional Cadence
Explosions in steep discounting coupons
Changes in how brands target customer cohorts
Captures in subject line aggressiveness
Our team is laser focused on generating the industry’s most accurate quantitative promotional trend data for nearly 200 brands. Our data scientists, natural language processing python developers, email systems experts, software engineers focus on creating the most robust insights in how brands are communicating with customers and leads. Random Walk’s focus is not telling our institutional investors how to do invest, but instead providing them with very clear quantitative measurable data visualizations. Specifically, we deliver a promotional ensemble that provides a picture of potential trend changes and inflections. Our near term objective to dramatically improve our promotional signals by creating brand by brand business logic to truly help investors understand what constitute a steep discount, an extended sale, a flash sale, an unexpected promotion and more.
Greg Robin is the founder of Random Walk. He has over twenty years in finance and has been involved in delivering big data insights to investors long before it was popularized on the street. He has a background in computer science with a graduate degree in distributed systems and has a background in search engine optimization having worked with over a dozen publicly traded companies. On the finance side Greg understands the needs of his clients as he has been providing insights over the past decade and previously held his research analyst series 86/87, series 24, series 7, series 4. Currently Greg also serves as the Product Manager for the soon to be released promotional insights dashboard working with a network of developers on the business logic of classifying, filtering and categorizing nearly 4 million emails from almost 200 leading brands.
Stephen McMurtry leads the technology process at Random Walk. He holds a BSc in Physics and Mathematics and a Masters of Applied Science. He has more than 4 years of industry experience creating mathematical models and preparing analysis to help others make data driven decisions. Stephen has produced data visualizations for the web that have been viewed more than one million times.
Timothy Gillihan leads the forecasting process, projecting key financial metrics based on Random Walk’s proprietary data. He has over ten years of experience analyzing publicly traded companies across all industries and regularly testifies as an accounting and economic expert witness in federal and state courts. Tim has interviewed hundreds of C-level executives regarding accounting practices, financial results, and expected future performance. Extensive knowledge of industry benchmarks and performance standards.
To help protect our clients’ edge we maintain a narrow distribution. Give us a call to see if we can work together.
Random Walk Financial
PO Box 7138
Rancho Santa Fe, CA 92067
email: sales AT ranwalk DOT com