As the calendar year draws to a close, we usually take the time to reflect upon the various trends and technologies that emerged and the impact they had on their respective industries. When it comes to E-commerce, one of the most intriguing trends that can be seen is the rise of ROPO (Research online, Purchase offline). While it can be claimed that this behavior has always existed, it is perhaps the increased ability we now have to track this behavior that has put it in the crosshairs of E-commerce strategists everywhere.
One of the biggest hurdles when it comes to convincing your customers to buy directly from your website is the fear of not getting the perfect product; the jacket that doesn’t look as good on you as it does on the website model, or the shoe that is just half a size too big or small. While the initial attempt to alleviate these fears was tackled with offerings such as ‘free returns’, which worked to an extent, the fears are still very much real.
Brick & mortar stores were so busy trying to make the shift to E-commerce in order to cash in on the enormous savings and profit margins they didn’t realize that the answer was not to try and replace their existing business model with an online one, but to enhance it.
As technology has evolved, it has become increasingly easier and more effective to close the loop on your online marketing spend, and see which users you were able to convert, either online or offline. With a vast majority of point-of-sale systems now with the ability to request a customer’s email address in order to send them a receipt, or enroll them in a loyalty program, the data can be used to combine with the online marketing campaign data to get a clear picture of the amount of times a specific person has seen or interacted with your advertisement online which eventually led to them purchasing your product in a store.
With the availability of such information and the growing influence / accessibility of machine learning, marketers have an extremely powerful tool at their disposal. Through marketing & re-targeting pixels littered across all the popular websites & apps that we use daily, to the information available through the point-of-sale system in the offline world, digital marketers can build a complete customer profile and their purchasing habits with respect to the information shown to them on a regular basis. Based on this valuable data, machine learning algorithms are able to identify patterns and behaviors that have a high success rate and potential to lead to conversion.
As it turns out, these findings are not what you may expect. The traditional marketer might jump to the conclusion that bombarding the user with more & more ads will lead to conversion. While this can be true in some cases, the ROI on these tends to not be as fruitful, and sometimes this strategy can yield negative results. It turns out that a recent trend of being informative and educational tends to resonate a lot more with the prospective customers, and they end up being more likely to buy from you once they are in the store and faced with a choice of multiple brands.
A brand that does this really well is The Body Shop. We recently design & developed a custom e-commerce website for them which not only provides all the features that you would expect in a fantastic online shopping experience, but also a plethora of sections which aim to inform, educate and help people learn about organic products, their importance and effects on the human skin, and how to take care of yourself.
This strategy of being helpful to their customers beyond anything else has worked wonders for The Body Shop, as the data suggests that their customers are fiercely loyal to the brand when it comes to offline purchases made after being exposed to the brand’s online efforts.
This is just one of many insights that can be gathered through A/B testing different strategies and their measuring results. With machine learning algorithms mining immense amounts of data to bring this intelligence to the forefront becomes a breeze.
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2019 is going to be a big year for E-commerce thanks to the massive rise in the technology available at everyone’s fingertips. The successful ones will be measured by their willingness to adopt new technologies and keep an open mind to new strategies. With machine learning and artificial intelligence available in abundance, there is no excuse left to not make data-driven decisions that lead to measurable results.