The challenge
Account openings are a key growth goal for a securities brand, which uses conversion ads to reach potential investors and grow market share. But market volatility and the limits of ad platforms’ machine learning had stalled growth. Breaking through and getting more from machine learning was the challenge.
Media strategy
Even with a single goal, account openings, results swing widely for many reasons. To understand the external factors, CloudAD started with GA data, studying how campaign periods and hot or quiet stock markets related to conversion ad performance. We found that market conditions and brand campaigns were the key drivers, and adjusted the media mix and budget by season and campaign: reach as many potential investors as possible when demand is strong, and control acquisition cost when demand is weak.
How we did it
- Step 1: data insight. Using social listening tools and interviews with the brand, CloudAD mapped peak and off-peak seasons in the stock market and the timing of brand campaigns to keep track of the market and competitors, and found a strong link between market conditions and ad costs, confirming our hypothesis. Knowing the key factors was not enough; we also needed to know how much they affected results. We added GA path length and conversion cost analysis and found that during hot markets and brand promotions, more users opened an account within three interactions, and account opening cost was up to nearly 50% lower. We defined two scenarios with different goals: in hot markets and promotions, grow the number of new accounts; in cooling markets and outside promotions, control acquisition cost.
- Step 2: media planning. In hot markets or promotions, paths are short, costs are low and motivation is strong, so CloudAD recommended growing the number of new accounts, raising the share of budget for proactive media such as display ads and forum word of mouth to reach more potential investors and increase market share. When markets cool or no promotion is running, paths are longer and costs higher, so the goal became controlling acquisition cost: the same mix of proactive and conversion media, with a larger share for conversion media such as search ads to meet the brand’s cost targets.
- Step 3: ongoing optimisation. CloudAD used GA assisted conversion reports to evaluate proactive and conversion media by source and medium, deciding which media to keep and adjusting budget shares. For newly added media, we compared overall performance and volatility before and after adding them and kept optimising, delivering steady growth and stronger conversions.
Results
- 2.7 times more new customers
- Customer acquisition cost down 20%
If you need help implementing or analysing GA4, get in touch.
