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Real Time Profiling
How to convert first time visitors into buyers
Online shopping is getting increasingly common. Lots of articles are less expensive in the online stores and there are easy ways to compare prices of merchandise over the net. However, customers still prefer to spend a significant amount of their money via traditional channels such as “offline stores”. What’s the reason that most people still favor department stores purchases over Internet-shopping? The key element is human interaction: Customers feel the need of interacting with “real” people, try things out and get advice from sales people. Internet-shops are currently lacking that “human-interaction” component.
Online shopping is getting increasingly common. Lots of articles are less expensive in the online stores and there are easy ways to compare prices of merchandise over the net. However, customers still prefer to spend a significant amount of their money via traditional channels such as “offline stores”. What’s the reason that most people still favor department stores purchases over Internet-shopping? The key element is human interaction: Customers feel the need of interacting with “real” people, try things out and get advice from sales people. Internet-shops are currently lacking that “human-interaction” component.
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Although the answer is pretty simple, it is difficult to overcome this disadvantage of online stores. It’s not easy to “humanize” an online shop, but several of the big players have already taken first steps in the right direction.
The “humanizing” of a website can be quite expensive and furthermore it’s not a differentiation factor anymore. At present the question is, how online stores can maximize customer value, and this from the very first visit of the potential customer. It frequently happens that filled shopping carts are not checked out and that first-time online customers leave the site without buying anything. Is there a way to overcome the “cautiousness” of online buyers?
The answer is real time profiling (RTP): knowing who your customer is right from the very beginning, like the salesperson that can read the customer mindset and classify him the very minute he enters the store. Real time profiling is monitoring the moves of a visitor on a website starting immediately after he entered it. By analyzing his “online behavior” the potential customer can be classified to one of the pre-defined profiles.
Every time a new customer enters a site, there is not enough data to make a more detailed assessment of his buying patterns and preferences. Hence, the best strategy is to start with a reduced number of more general profiles- maybe 3-5- and match the customer to one of them. Then the classification should change dynamically based on the further steps/actions he undertakes while being connected to the online store. The analysis of the customer behavior should be done in real-time right from his first visit. Online historic analysis may be useful, but it helps only if the customer returns. And he may not come back.
A customer enters a clothing online-store and starts browsing through the offers. If he goes directly to the trendy stuff and the new collections he is classified as “stylish”. Others who go directly to the sales and clearance pages are “bargainers”. Looking at the more exclusive items of the store implies the customer is someone who is ready to pay a premium for higher quality, therefore he is a “premium” customer. This is just an example of a possible set of profiles for a clothing online shop. The set can be extended if there are good enough reasons to do. However the key to this approach is to match the first-time visitor to a profile right after he enters the store.
It’s not the real time profiling only that guarantees the success but actually its mixture with several other electronic customer relationship management tools (eCRM). The best results are gained if RTP is used together with an interactive online chat tool. If the customer needs assistance he can press a button which leads him to a customer service representative or a bot (autonomous software that simulates a human activity). This one has access to the customer’s profile. Therefore he/ it can provide tailored answers and hints.
Most of the interactive customer-service tools, which include a chat module, give the salesperson the opportunity to contact the visitor directly. Of course it’s up to the customer to decide if he accepts a chat or not. However this way the customer representative can act in a proactive manner. As an alternative telephone support may be used, but then the sales representative can’t act proactively. By knowing the profile and preferences of the visitor/potential customer, the agent can make cross selling offers. Given the information already gathered on the visitor, the offers are targeted and reach a higher acceptance level.
Major eCRM tools have already added RTP or are about to do so. Following this trend manufacturers of smaller software packages of CRM have also recognized the need of realtime data.
By offering a fast proactive and efficient customer service - supported by real time profiling -visitors can be turned from “browsers” to buyers at their first visit of the online store.
The “humanizing” of a website can be quite expensive and furthermore it’s not a differentiation factor anymore. At present the question is, how online stores can maximize customer value, and this from the very first visit of the potential customer. It frequently happens that filled shopping carts are not checked out and that first-time online customers leave the site without buying anything. Is there a way to overcome the “cautiousness” of online buyers?
The answer is real time profiling (RTP): knowing who your customer is right from the very beginning, like the salesperson that can read the customer mindset and classify him the very minute he enters the store. Real time profiling is monitoring the moves of a visitor on a website starting immediately after he entered it. By analyzing his “online behavior” the potential customer can be classified to one of the pre-defined profiles.
Every time a new customer enters a site, there is not enough data to make a more detailed assessment of his buying patterns and preferences. Hence, the best strategy is to start with a reduced number of more general profiles- maybe 3-5- and match the customer to one of them. Then the classification should change dynamically based on the further steps/actions he undertakes while being connected to the online store. The analysis of the customer behavior should be done in real-time right from his first visit. Online historic analysis may be useful, but it helps only if the customer returns. And he may not come back.
A customer enters a clothing online-store and starts browsing through the offers. If he goes directly to the trendy stuff and the new collections he is classified as “stylish”. Others who go directly to the sales and clearance pages are “bargainers”. Looking at the more exclusive items of the store implies the customer is someone who is ready to pay a premium for higher quality, therefore he is a “premium” customer. This is just an example of a possible set of profiles for a clothing online shop. The set can be extended if there are good enough reasons to do. However the key to this approach is to match the first-time visitor to a profile right after he enters the store.
It’s not the real time profiling only that guarantees the success but actually its mixture with several other electronic customer relationship management tools (eCRM). The best results are gained if RTP is used together with an interactive online chat tool. If the customer needs assistance he can press a button which leads him to a customer service representative or a bot (autonomous software that simulates a human activity). This one has access to the customer’s profile. Therefore he/ it can provide tailored answers and hints.
Most of the interactive customer-service tools, which include a chat module, give the salesperson the opportunity to contact the visitor directly. Of course it’s up to the customer to decide if he accepts a chat or not. However this way the customer representative can act in a proactive manner. As an alternative telephone support may be used, but then the sales representative can’t act proactively. By knowing the profile and preferences of the visitor/potential customer, the agent can make cross selling offers. Given the information already gathered on the visitor, the offers are targeted and reach a higher acceptance level.
Major eCRM tools have already added RTP or are about to do so. Following this trend manufacturers of smaller software packages of CRM have also recognized the need of realtime data.
By offering a fast proactive and efficient customer service - supported by real time profiling -visitors can be turned from “browsers” to buyers at their first visit of the online store.
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