Customer Forecast, an Industry First
A common challenge marketers face is an inability to tie top-funnel brand investments to bottom-of-funnel outcomes. There is a glaring gap between sales lift and brand lift, and that missing link is the customer. You can now tie your brand campaign to the number of new customers acquired or retained and measure outcomes of brand advertising that has been validated by real sales data.
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The Upwave Difference | Customer Forecast
Upwave’s Customer Forecast metric was developed for marketers to gain an understanding of which media tactics are driving future customer growth, without relying on short-sighted metrics like Multi Touch Attribution or sales lift. Finally, get quantifiable results to prove out your investment in brand.
Close the gap between sales and brand lift
The central intended outcome of brand investment is to increase the propensity of those reached by campaigns to become customers. With Upwave’s Customer Forecast tool, marketers can now see the number of customers they’ve acquired and retained who have been exposed to their brand campaign. Tying top of funnel metrics to bottom of funnel outcomes and finally offering the missing piece that connects brand movement to revenue when paired with customer lifetime value (CLV).
Don’t undervalue the impact of your brand campaigns
Customer Forecast is able to reveal the actual length of time between exposure(s) to a brand campaign and becoming a customer – helping to better understand your sales cycle and measure outcomes of brand advertising in a way that hasn’t existed traditionally. Backward-looking metrics like sales lift and MTA (originally designed for direct response campaigns) capture short-term sales impacts, severely under-valuing TV and brand campaigns that are intended to drive business outcomes both mid- and post- campaign.
Faster and more granular than MMM
Customer Forecast brings longer-term impact traditionally available as a part of Media Mix Modeling forward to the campaign-level in real-time. Top-down metrics like MMM better value TV and other brand campaigns, but are too slow and coarse-grained to support optimization and planning decisions.
