As a proud data partner on Snowflake’s new Retail Data Cloud, we’re highlighting Sunday, an innovative lawn care brand using Crisp and Snowflake to uncover advanced insights that drive their one-of-a-kind customer experience.
A product powered by data
When it comes to data, Sunday is in a league of its own. Launched in 2019, Sunday leverages technology to offer customized lawn care plans and products focused on non-toxic ingredients. It’s all possible thanks to data: information about location, soil type, and climate helps each customer find the best way to keep grass thriving and pests at bay, all while protecting the planet. Sunday has grown exponentially since launching, raising a $50M Series C funding round late last year.
Sunday’s VP of Technology Jesse McClure thinks about data from all angles: there’s data that powers Sunday’s product recommendations, and also internal data to drive the team’s sales and marketing functions. This includes information about topography, local weather patterns, soil analysis, digital marketing, and sales data, all at a vast scale.
It’s all possible thanks to Snowflake, which Jesse describes as “the brain of everything we do.” His first priority is aggregating the data in one place, from which more sophisticated analytics (like machine learning) can follow. “Our data set is so massive, and sometimes counterintuitive. With machine learning, the data science team can find all these links and commonalities in the data that no one else would be able to pick up on,” he explains. For example, the team had a hunch that more rain would make for happier customers. But by analyzing weather patterns and sales data together, the team found that it was actually a source of stress, because customers can’t apply liquid fertilizers when it’s actively raining. With this insight, Sunday can support gardeners with guidance and advice for lawn management during a rainy spell.
Omnichannel presents a new challenge
Sunday is a direct-to-consumer company at heart, offering guidance and resources to build a lasting relationship with customers. But recognizing that retail stores are still an important part of the home improvement buyer’s journey, the team decided to launch at Lowe’s and other major retailers– officially becoming an omnichannel brand. Sunday imagines retail as the gateway that leads to a deeper relationship with every customer, which requires an understanding of the interplay between in-store and online shopping, as well as the impact of digital engagement in stores.
To bring those two sides of the business together, the Sunday team needed to aggregate their data in Snowflake. That’s when they found Crisp.
Sprouting up insights
Now, Sunday uses Crisp to seamlessly analyze their retail data in Snowflake, where it can be combined with existing data sets for truly unique insights. “Snowflake is now where e-commerce and retail all come together,” Jesse explains. “Those are very different channels, but knowing that customers from each are in the same geographical area, we can see an interesting interplay between the two.”
For example, Sunday recently began marketing through media like video, podcast, and radio, and this cohesive data set is helping them target campaigns and measure performance across the business. At first, the team wasn’t sure if advertising would lead to a direct uptick in retail sales, but they’re now seeing an impact and further exploring how to leverage retail and digital together. “This is the first year we’ve really had that data, and we’re eager to see what other conclusions we can draw,” Jesse notes.
“On our own, we would have been wandering through trying to piece our retail data together. From day one, Crisp gave us such a huge return on investment.”
Jesse McClure, VP of Technology
The piece tying it all together is geographical data across channels, which is critical to Sunday’s peak season: the start of spring. Unlike typical busy seasons, such as the holidays, Spring rolls out slowly across the US from South to North – so Sunday can learn from sales patterns in Southern climates and apply lessons for Northern locales. This is possible thanks to the way Crisp augments store location data, adding coordinates onto store addresses to enable mapping and analysis. Sunday already has GPS coordinates for DTC customers, part of offering their customized solution – but with Crisp, Sunday can also leverage this format in Snowflake alongside the DTC data. The result? A holistic analysis of sales patterns by geography.
Jesse says that Crisp has made the retail team more data driven, helping them come up with more nuanced questions to drive strategy. “On our own, we would have been wandering through trying to piece our retail data together. From day one, Crisp gave us such a huge return on investment.”
The retail team uses Crisp’s dashboards for daily snapshots, trends, and decision-making, then rely on Snowflake analysis for additional insights. They pay close attention to what categories (fertilizer, pest control, etc.) are selling, and how those patterns tie back to weather data – which they can get thanks to Snowflake’s data marketplace. Laying retail data over weather patterns enables the retail team to plan promotions and orders around expected trends…and yes, even predict the weather at times.
Ready for spring
Ultimately, having all of their data in the same place has helped make the two sides of Sunday’s business feel more like one. “Crisp has actually brought the team together,” Jesse reflects. “We’re a single entity trying to drive toward one mission.”
Jesse explained that a quick set up process and clean, usable data was hugely important for a fast-moving startup. “Crisp’s data modeling has saved so much time and energy,” Jesse says.
Sunday’s data-driven innovation isn’t slowing down any time soon. They just rolled out a live plant line on GetSunday.com, which recommends specific plants based on a customer’s location and hardiness zone, along with preferences like care requirements and pollinator-friendliness. The live plants are shipped straight to your door when it’s the right time to plant.
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