You can build what you think is the best store in the world. But if you fail to align it with standard online customer behavior, you won’t make many sales.
There is an unbelievable amount of information you need to know to sell online.
You must learn everything about your products and niche you want to operate in. You need at least some basic understanding of the technology behind the store too. Then there’s marketing: you must know how to promote the store. Chances are that you will be doing that on your own for a good while.
But a crucial aspect of ecommerce gets often lost among all this information – your customers online behaviour. Part of the reason is that it seems obvious – someone lands on your site, finds products he or she wants and providing the price is right, shipping is within reason and the product is available of course, buys.
Unfortunately it’s not that easy. There is much more to the user buying process than the 4 stages framework commonly discussed:
There are underlying processes that happen during each of those stages. If you are thinking of starting up your store, it’s crucial that you learn about them.
In 2012, two management professors Ujwala Dange and Vinay Kimar from Priyadarshini Engineering College and S. B. Patil Institute of Management respectively proposed a model for online customer behaviour. It is not the first time a model like this has been developed but I found theirs to be most relevant to customers of today.
The FFF model takes into consideration internal and external factors affecting consumer buying behaviour. It then proceeds to discuss various filtering elements customers will apply to make a selection of a store to purchase from and revised filtered buying behaviour based on their final selection.
Graphically the model representing customer journey to purchase looks like this:
1. Factors
Starting from left, the first element Kimar and Dange identified are factors that motivate customers to buy products or services online. They divided them into two categories: external and internal.
The external factors are the ones beyond the control of the customers. They can divide into five sectors: Demographics, socio-economics, technology and public policy; culture; sub- culture; reference groups; and marketing.
Internal factors are personal traits or behaviours and include attitudes, learning, perception, motivation, self image, and semiotics.
Based on such factors customer develops what Jagdish Sheth, a professor of marketing at Emory University defined as two distinct types of buying motives: functional and non-functional.
The functional motives relate to consumer needs and could include things like time, convenience of shopping online, price, the environment of shopping place (i.e. couch buying), selection of products etc.
The non-functional motives relate more to the culture or social values like the brand of the store or product for instance.
2. Filtering Elements
Kimar and Dange recognized security, privacy and trust as three hurdles to online purchases. Customers use these three factors to filter their buying choices and decide on the final selection of stores they are willing to buy from. In other words, if your store doesn’t pass your customers’ security, privacy and trustworthiness criteria, they won’t buy from you. Even if you are cheaper.
Compared to traditional brick and mortar shops, online shopping carries more risk during the purchase process. Customers recognise online as a high level risk purchase and have become aware of what might happen with their data online. They use that knowledge now to filter their purchase options by 3 factors:
It’s an unfortunate characteristics of the internet that information there could be easily lost or stolen. Your payment details or personal information could easily be retrieved from a database it is stored in by the shop for instance, as we have seen recently with few major security breaches.
Customers are growing more aware of the dangers of stolen data from the web. And they filter their purchasing alternatives against security criteria.
Another type of risk online is having personal information handed over to or stolen by 3rd party companies to send unsolicited emails and spam to customers. Even though the results of privacy breaches may not be as severe as losing your financial data, it can still cause a great deal of frustration and diminish trust in stores.
A lack of trust in a store’s privacy policies is a serious obstacle for many customers. Similarly, many customers look for reassurance that their data will be protected and not handed over to any 3rd parties for further use in marketing.
Online trust is essential in building any relationship with customers. There seems to be however a diminishing trust in online merchants. This is especially true when it comes to smaller, niche stores. Customers focus on Amazon and other giants, shops with big brands behind them and don’t apply the same level of trust to a smaller shop. So if you run a store selling bike storage for instance, you should work hard to build a high level trust among your customers to be picked up for the order.
3. Filtered Buying Behaviour
The last element of the model covers what authors call the filtered buying behaviours, a set of expectations and motives revised by the filters we discussed above.
Knowing and understanding the FFF model is not enough; you should act on it when designing your store. Here are the key takeaways you should remember:
Next you should ensure that you overcome your customers’ fears over security and privacy by
Creative Commons image: Serge Kij / Flickr
Tagged consumer, consumer behavior, eCommerce, online, privacy, security
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Nice Article but I think user interface will also help enable sales online, server speed, helpful tool tips and creating a sense of urgency.
It needs perfection at every level and that is why very brands make it online.
Thanks
Ajay