Data Foundations for scaling cosmetic and personal care brands
You're growing rapidly, but can your data infrastructure and reporting keep up?
Our Data Foundations service unites your data into a trusted source, embeds AI capabilities and produces custom dashboards you'll actually use.
Your data sprawls across retailers and you may have 1000s of SKUs. We'll unite for one trusted view.
Beauty and wellness brands suffer retailer sprawl early on; TikTok shop, Boots, Superdrug and Amazon all output in different formats and with different delays. The problem is multiplied when you consider the volume of data due to many different SKUs!
We'll set you up for greater growth and complexity with a data warehouse and automated ingestion pipelines, so data is up-to-date and unified without ongoing lift from you.
Visibility is hard to properly attribute across influencers, paid and retailers. We'll decode it.
The market is crowded so every pound of media spend needs to pull its weight. Whether you're managing complex influencer programs (like we did with Amazon and Buttermilk), exploring OOH for the first time or wondering whether your retailers may be cannibalising your D2C sales, we can help.
The path to trusted and rigorous analytics starts with strong data foundations. Book a call to see how.
“We chose D1D over the others because I didn’t want to get locked into yet another platform that wouldn’t give me a custom solution & I wanted a better way to measure attribution than GA4. We love working with Day1!”
Jamie Freed
Vieve Beauty, Chief Customer Experience Officer
Why scaling personal care brands need Data Foundations.
Repeat purchases are key to sustainable revenue
But in order to understand your repeat purchase data, you need multiple data sources united at the customer level.
Heavy seasonality and promos distort your data.
Without having a clean real-time view of your data, decisions about promos are guesswork, particularly around Black Friday!
Inventory management relies on forecasting.
Viral moments can drive stockouts or products can exceed their shelf-life. Proper forecasting relies on trusted data.