Retail marketing analytics is the process of leveraging data to understand what drives sales and how customers behave to make better business decisions. In the last couple of years, as the COVID-19 pandemic impacted the retail industry, there were dramatic shifts in the way we allocate marketing resources in retail to most effectively improve overall customer experience and sales.
Have you found yourself at times shopping online, in-store, and with curbside pickup at the same store? If you said yes, you are not alone – according to Carat Insights, omnichannel spending has sharply increased, and half of all consumers use multiple channels for shopping.
With omnichannel shopping as the next big trend in retail, retail marketing analytics optimization must adapt to new requirements. It means dealing with complexity and massive amounts of data from disparate sources such as websites, point-of-sale, call centers, consumer feedback – making data science and analytics crucial to optimizing marketing efforts.
5 Ways to Use Data Science to Optimize Retail Marketing Analytics:
1. Gain visibility across all campaigns and channels
Customers have exposure to advertisements across multiple touchpoints, including websites, email, billboards, television, print, social media, and in-store. In this multi-touchpoint environment, we need to gain visibility and think holistically. The first and most crucial step in optimizing retail marketing is automating data collection and merging analytics reports across all marketing channels and campaigns to enable holistic study.
2. Attribute conversion to the right campaigns and channels
Omnichannel marketing professionals face a major challenge in marketing attribution or understanding which campaigns and channels caused a customer conversion. Accessing the correct data at the right granularity is crucial to attribute conversion correctly. Depending on the use case, first-touch, last-touch, multi-source, or weighted multi-source or customized models may be the best approach for attribution.
3. Optimize cross-channel return on investment (ROI)
Once we understand which channels and campaigns contribute to conversion, the next step is to boost the quality of marketing actions for maximal return on investment. Using mathematical optimization can help optimize marketing spend after merging omnichannel, multi-campaign data and performing marketing attribution analysis.
4. Understand customer conversion and lifetime value, and acquire customers, even with missing data
The best way to acquire valuable customers and increase sales is to understand the time to customer conversion and customer lifetime value to help engage appropriately. Data science and analytics methods are crucial to predict and maximize acquisitions and conversions accurately. Clustering can define persuadable customer segments to target and identify similar customers even when data is missing. We developed, via Aimpoint Labs, an open-source tool based on novel research, apd-crs can predict time-to-event for conversion or churn, even when time-to-event information is missing for a sizable percentage of customers because the event has not been reached.
5. Drive loyalty by optimizing the customer experience
By using data science to analyze the customer journey, understand key segments or personas, make recommendations, track key metrics such as Net Promoter Scores using Natural Language Processing, and perform A/B or multivariate testing, we can understand key pain points and preferences. A variant of A/B testing, multi-armed bandit approaches can help predict the effect of campaigns on new customers and dynamically allocate web traffic to product variations that perform well. With optimized marketing analytics, you can drive engagement and loyalty by translating clicks and views into the best-personalized experience for customers.
Aimpoint Digital – Your Partner in Optimized Retail Marketing Analytics
Aimpoint Digital is committed to helping all industries, big and small, unlock the potential of data analytics to transform their day-to-day operations.
If you would like to increase your profits using optimized cross-channel retail marketing analytics, contact us through the form below to speak with our data science, analytics, and optimization experts.