At the Infant Nutrition Division of Nestlé Taiwan, data-driven attribution is being used to drive an overall increase in conversion rates and to boost overall orders and turnover. It’s also helped Nestlé Taiwan gain insights to consumer conversion pathways, move away from the last-click mindset, and develop better marketing strategies for connecting with niche audiences like expectant parents.
Imagine you’re an expectant parent with your first child on the way. You’re probably overwhelmed, anxious, and excitedly researching how to prepare for your new baby. You might turn to your parents or grandparents for advice, but the internet is likely your go-to source for information. Nestlé Taiwan’s Infant Nutrition Division is on a mission to help these new parents, provide them with resources to support them throughout their pregnancies, and then, convert them into Nestlé customers. But with declining birth rates in Taiwan, the division faced a challenge when attempting to market to this shrinking market.
Implementing DDA to engage with future moms across the spectrum
To better identify with new moms, we worked with Nestlé Taiwan to implement a data-driven attribution (DDA) model to gain more comprehensive insights into their consumer journeys, determine the real value of each touch point, and maximize the conversion of prospects. Powered by machine learning, DDA helped the brand understand the true click value of each keyword in its campaigns, gain more comprehensive consumer insights, and avoid the blind spots associated with the last-click attribution model.
Currently, more than 90% of Taiwan’s marketers still use single-touch attribution, focusing on the last click to measure campaign performance. However, it takes at least 3.5 clicks, on average, before a consumer makes a decision, which makes measuring the marketing performance of a campaign using only the last touchpoint misleading — especially when trying to engage with moms-to-be.1 These women may be at different stages of their pregnancy research and may engage with brands in different ways depending on what they’re looking for.
DDA enabled Nestlé Taiwan to learn which keywords during the consumer journeys of these moms-to-be provide additional conversion value. For example, studying the journeys of people who signed up for the Nestlé Maternal Nutritional Supplement could potentially uncover new opportunities.
Let’s say there’s a search path that shows a 2% conversion rate from consumers who started with general keywords like “mother pregnancy and breastfeeding” and then clicked through to the brand keyword. And a second path that uses different general keywords such as “what to eat during pregnancy” that could bring a 3% conversion rate. By comparing these two paths, Nestlé can use DDA to uncover the additional value the term “what to eat during pregnancy” could bring.
Through DDA, these more accurate conversion attributions improved Nestlé Taiwan’s ability to reference customer journeys and bid on keywords that bring more value, helping to lower CPA and further drive conversion rate.
“Thanks to our cooperation with Google, we have successfully implemented machine learning and seen its value to business operations.” — Sheeny Liao, digital marketing executive, Nestlé Taiwan Infant Nutrition Division
Ditching the last-click attribution model to boost conversions
After implementing DDA, Nestlé Taiwan’s marketing campaigns saw a 19% increase in conversions, a 7% increase in conversion rate, and a 10% decrease in conversion costs. More importantly, Nestlé Taiwan was able to step away from the last-click mindset, gain real insights into customer conversion paths, and develop better marketing strategies to find new conversion opportunities for its Infant Nutrition Division.
Consumer trends are in a state of constant flux, and marketers today must learn to glean valuable insights from the flood of data. Having the right information allows marketers to measure campaign performance accurately and effectively, and embracing and testing new technologies can enable brands to create more effective results.
