Customers
What good looks like
CPG brands use Scout to unify their data and automate the workflows around it. The fastest teams take on 15x the workload.
~2%
Revenue recovered, across the board
50%
Cut in supply chain out-of-stock issues
45 min
Weekly reporting time, down from 8 hrs
- Snack brand
Weekly reporting went from eight hours to 45 minutes.
$425k year-one value
- Personal care brand
A three-person team running like an analytics department.
$105k year-one value
- Beverage brand
Used promotions as a strategic investment for increasing sales.
~$3.07M/yr identified value
- Pet food brand
A 50% reduction in supply chain issues, recovering lost sales.
~$2.4M year-one value
What customers say
Less time wrangling, more time deciding
“Scout cut our category review prep time significantly and armed us with competitive insights that would not have been surfaced in our standard data review process.”
Director of Sales· Heirloom Coffee Roasters“This has shown me so many things about my stores I did not know before. Stocking a few products that were selling well in some locations and not carried at all in others has lifted our revenue by more than 2%.”
Owner, regional grocery retailer “We used to spend the week before every category review pulling numbers by hand. Now most of the deck is written before we sit down.”
Category manager, natural foods brand “I asked a question the way I would ask a person, and got the answer with the rows behind it. My team stopped waiting on me to run reports.”
VP of Sales, snack brand
Results
What we have done for customers
A sample of the work, across retailers and brands at different stages.
| Customer | What Scout did | Result |
|---|---|---|
| Regional grocery retailer, 40+ stores | Surfaced products selling well in some locations and not carried at all in others | Revenue up more than 2% |
| Specialty coffee roaster, natural channel | Automated category review prep across syndicated and retailer data | Review prep cut from days to hours |
| Better-for-you snack brand | Modeled deduction cost into trade spend before each promotion ran | Promotions priced on true net revenue instead of gross |
| Beverage brand, mass and club | Modeled post-promotion lift to separate incremental volume from baseline | Trade spend shifted onto the promotions that actually lift |
| Household goods brand, multi-retailer | Scored distribution gaps store by store across every retailer feed | Hundreds of store-level placement opportunities ranked by value |
“My data used to live in multiple tools, most of them clunky. Trade-spend reconciliation that took hours every week now takes fifteen minutes, and I spend that time making decisions instead of preparing data.”
Tell us what you’re working on
A 30-minute conversation to scope fit. Pick a time that works for you.