Salesforce signed an agreement to acquire Braze at approximately $5.66 billion in enterprise value, emphasizing its ability to turn live customer behavior into personalized engagement. The acquisition has not yet closed.
The promise sounds straightforward: fresher data, faster communication, more sales. At Sellf, we evaluate that promise through three dimensions:
- Signal: Last month’s purchase can reveal preferences; today’s cart activity signals current intent. Data’s useful life depends on the question it answers.
- Delay: Measure the time between behavior, decision, and intervention. Compare immediate and delayed responses to quantify the contribution profit lost through waiting.
- Incrementality: Compare against a randomized control group receiving no intervention, accounting for discounts, messaging, and technology costs. Track repeat purchases and retention, too.
Consider a hypothetical example with equally sized randomized groups: a TRY 1,000 basket generating TRY 400 in contribution produces TRY 80,000 across 200 orders. With other costs unchanged, a 10% discount that increases orders to 220 reduces contribution to TRY 66,000. More orders, yet TRY 14,000 less contribution profit.
In our growth engineering approach, speed earns its value through additional profit.
What profitable behavior did this intervention create that would not otherwise have happened?