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How Real World Customer Interaction Data Can Improve Online Retargeting

How Real World Customer Interaction Data Can Improve Online Retargeting

Established advertising solutions fail to bridge the gap between the online and offline customer experience. But real world customer interactions are of the utmost importance to retailers, as more than 90% of all shopping still occurs in physical stores. 

In order for advertisers to truly optimise their approach to consumers, they are going to have to understand how they shop offline. There are three key reasons why: 

1. Offline shopping behaviour data will allow retailers to clearly define and segment their customers based on their loyalty.

Only by understanding the differentiation in their customers’ visit frequency and duration will retailers be able to optimise their ads. Most retailers today simply have no way to measure their average customer loyalty let alone its variation amongst customer groups. They are in dire need of appropriate customer segmentation tools, especially if they do not have loyalty apps or programs.

Retail Analytics solutions can provide marketers with that necessary customer transparency. By utilising movement-tracing technology, retailers can gather data about how, where, and with what customers interact in their stores. That data allows retailers to calculate a precise measure of their customers’ interest in specific brands, goods, or services. Only once they know this information are retailers truly able to optimise the omnichannel accretion for each of their various customer segments.

2. Offline shopping behaviour data enables retailers to maximise advertising ROI by allowing them to target the optimal customer segment, with the optimal advertisements, on the optimal device.

Most marketers today are unable to clearly define and target their key audiences. They waste huge amounts of money and have massive scatter losses by focusing on maximising their number of impressions instead of focusing on their quality. But by utilising their customer segments’ offline shopping behaviour, marketers are able to effectively increase customer conversion while cutting the number of necessary impressions to do so. 

That is because data reveals the most lucrative customers for a given brand and the impression most likely to convert them; based on behavior data, brands can determine exactly how lucrative customer A is and that the most likely way to convert them is to send them ad B for product C on device D at time E. 

This way, marketers pay for only the impressions that matter. Furthermore, if they know a consumer has purchased from a given store, marketers can effectively retarget those customers to make additional purchases across a retailer’s various omnichannel platforms. Most marketers know that the key to omnichannel success is to diversify their approaches to different customers, but until they know how those specific consumers behave offline they will not know the most efficient way to do it. 

This approach allows marketers to target their customers with more relevant and personalised ads than ever before. In order to retarget customers on an even more granular level, the geo-location insights about your shoppers’ visiting behavior, derived by Wi-Fi analytics technology, can be further matched with suitable other behavioural and demographic filters available on the market today. This will provide you with a maximum amount of relevant impressions and return on investment. 

3. Offline shopping behaviour insights allow marketers to calculate the precise ROI of their ads by revealing how many of their ad impressions result in consumers returning to their stores.

Marketers today know very little about the effectiveness of their ad impressions. They know roughly which impressions are more likely to lead to conversions than others, but they do not know how many conversions they ultimately have. But they can, if they trace offline-shopping behaviour. With that data it is possible to determine which and how many ad impressions a given customer has seen before making a purchase or visiting a store. Retailers can thus determine which impressions are more effective than others and use that information to further refine and optimise how they target their various customer segments with advertisements.

Conclusion

Most marketing activities today are inherently inefficient; marketers simply do not know enough about their customers to fully optimise their impressions. In order to fully optimise their ads, they need offline shopping behaviour data. For if marketers know where and how a given consumer has physically shopped they can determine the most efficient way to target their impressions to that customer and the most likely impression to retarget that customer to omnichannel shopping. Not until then will retailers be able to measure and increase their customer loyalty.

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Got a question or comment – tweet Tim @Tim_R_Wegner or comment on Twitter, Facebook or LinkedIN.

Tim Wegner

Tim Wegner

Tim Wegner is Founder and CEO of MiNODES, the leading Retail Analytics and Omnichannel Retargeting partner for stationary retailers and marketers. Prior to founding MiNODES, Tim worked at McKinsey & Company, consulting major retail clients ranging from consumer electronics, food, furniture, DIY to automotive all over Europe, focusing especially on novel Omnichannel and e-Commerce strategies. Further, he helped to advance the industry’s knowledge on global technology trends at the McKinsey Global Institute in San Francisco, including the impact of Big Data and the Internet of Things. Tim studied Physics at Imperial College London, MIT and the Technical University of Munich.

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