How to use data to grow in e-commerce?
12/08/2022 - kenadmin
Everything your customer buys and does online and offline can be stored, with permission. Who you are, what book you like to read, what your fashion preferences are, what products you bought last and how frequently you shop, ... If you want to be successful within e-commerce today, you must not only follow the trends, you must understand your customers, knowing them is not enough.
The limit of insights you can extract from it as a marketer is limited only by your own creativity. If you want to benefit from the growth within e-commerce and serve the group of demanding consumers, you have to smartly adapt to the changing circumstances. Embrace the possibilities of data, discover unique customer segments and use these alongside your online strategies to make a difference in the hugely competitive webshop world. Here are some ideas to get you started.
How buying power is your customer
Try to assess a customer's spending and buying habits. If you notice that a customer spends more than your average visitor, you can suggest more high-end products instead of the usual standard line or promotions. Customers who can only be convinced if the promotion is big enough, will be hard to convince to buy without promotion. Only if you give them a very pleasant shopping experience in the offline shop will they buy. Customers who buy regularly do not need to be pushed too hard (promotional) to fill their shopping cart.
Where does your customer live
This socio-demographic data with roots in the physical world often complements online algorithms. It can be useful to know whether your customer lives in an apartment or in a house with a (large) garden. Many customers will never make large -or volume- purchases when they have limited storage space. It's also hard to sell a garden set to someone who doesn't have a garden or patio but does have decorative materials. The neighborhood also usually says a lot about lifestyle characteristics and linkable needs. The demand for swimming pools, garden furniture and outdoor living products has skyrocketed since we have been doing more and more staycation. And under the motto "support your locals," people were encouraged during the corona crisis to support entrepreneurs in their own town or village. Also, send your online customer by the local physical store with authentic offerings.
Who is your client - who does your client live with
The transaction of a purchase is usually always handled at the individual level. However, it is very interesting to also know the family behind your customer. Many parents buy clothes for their children, grandparents buy gifts for their grandchildren. Cross-selling based on the basket can then lead to strange propositions. On the other hand, "gift buyers" may also be open to great gift ideas for other members of the family or household. Who do you all know within the family, what is the family budget and which channel is best for each member of the family?
What product preferences does your customer have
'Others also bought' or 'You might also find this interesting', clever algorithms that very often provide relevant suggestions. Again, try to combine all offline and online sales over a longer period of time. Many suggestions do not take this into account enough, so the power of the algorithm is lost (and too vague and broad suggestions are made). If you can, integrate click behavior as well. That way you get not only transactional but also aspirational baskets.
In addition to segmentation techniques, it is an absolute must continuous (real or near time), to have a data set available for each customer that reflects the buying and behavioral characteristics in many ways. For each customer there may be a different parameter that will determine his behavior or preference. This set of parameters includes buying information, how long has it been since the last purchase, among others. What is the recency and buying frequency per product category, how much does someone spend per category in the last period or years?
Is spending shrinking, growing or remaining stable? Are purchases being made from new categories? Which communications and channels are best responded to? How responsive is your customer by channel? What is the average discount at which someone buys, are there product preferences depending on buying online or offline? All these characteristics and many more are one by one parameters that can explain something about the behavior of each individual customer. And this evolves from day to day. Understanding these relationships is the next step to trigger-based programs and predictive modeling (propensity to buy / to act, churn, ...) Thus, content marketing is meanwhile being replaced by context marketing and micro-segmentation and personalization are more commonly used.
Single customer view platforms are today known as CDP (Customer Data Platform) and exceed the capabilities of CRM, MAT or DMP platforms. Stratics' Marketing Insights Platform (MIP) is one such CDP platform that not only offers Data gathering and 360° customer view capabilities but also includes strong data quality, deduplication and enrichment tools that give you quick insights at both individual and family levels of a customer.