Published 2026-08-15 · Last updated 2026-08-28
Data and AI consulting for ecommerce brands
Ecommerce brands using data and AI for attribution, inventory, and personalization—without buying a platform you cannot operate.
By Ralph Lehnert · · Team at Lehnert Ventures (Orlando & Bavaria)
Data and AI consulting for ecommerce brands is not a dashboard shopping trip. Brands already drown in Shopify reports, ad platform attribution fights, and vendor pitches for “AI” that means send more email. The bottleneck is decisions: what to stock, what to cut, and what to spend on next week.
Consulting fits when you have revenue and SKUs moving—but data work is a defined problem: attribution cleanup, demand forecasting, personalization that does not break ops, or CDP chaos before a peak season.
We build and operate growth companies—DM4Y, Rothsteiner, WeGrowHospitality—so recommendations tie to margin and ops, not vanity metrics. Compare generic startup data advice at data & AI consulting for startups.
- Name the commercial decision data should improve (margin, CAC, inventory—not “insights”).
- Audit sources: storefront, ads, email, warehouse, finance.
- Fix measurement before models; bad inputs make fancy AI expensive noise.
- Ship one use case with weekly review cadence.
- Expand only when operators actually change behavior from the numbers.
Service pages: data & AI consulting and ecommerce consulting. Sector portfolio: hospitality and consumer portfolio.
Book /contact?type=consulting when peak season or a platform migration is on the clock.
Frequently asked questions
Do you implement or only advise?
Hands-on consulting: architecture, implementation, and operating cadence—not slideware.
DTC food and consumer brands?
See Rothsteiner on the venture studio and hospitality and consumer portfolio.
What is not included?
We are not a managed ads agency by default—growth consulting may pair with DM4Y-style execution when scoped.