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B2B: Data Science and the Customer Experience

28th Aug 2017
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While retail has changed, evolving into a multi-headed creature encompassing web sales, physical premises and the influences of social media, one thing remains clear – examining customer data to understand their needs and predict their actions is vital.
Once thought of as B2C sales problem, B2B has been slow to embrace this trend, but with large companies such as Amazon and Google wading into the B2B market, you must have all the information you can to take on the big boys.

So, what can you do to get ahead of the game? Well, play to your strengths. Embrace customer service.

Data science in a nutshell

Responding quickly to change can help you outmaneuver big businesses. Where large-scale companies have to wait for interpreted data to filter down through the relevant channels before discussing a course of action and change is implemented, with smaller-scale operations this is a swifter process. Which means you can provide what your customer really needs before the big boys are out the starting blocks.

Using a combination of Google Analytics reports and information from their commerce platform to identify trends is common. This may be enough for some, but by using them alongside details directly gleaned from customers themselves you will achieve the best results. We are also seeing an increase in machine learning for B2C and B2B businesses, and embracing these trends is essential, otherwise, you face being left behind.

Customer classification

Understanding your customers is marketing 101, and while you may assume that your business attracts a certain audience, you may be surprised to learn that your assumptions are far off the mark when the data is analyzed. Modern analytics take out all the guesswork from the equation, so don't skip on this. Proper market analysis, with large enough scope and over a longer period of time, while costly at first, will save money in the long run by giving you right information on where to direct that marketing budget. Generally, you can start of with making some broad categories first, which pretty much apply to any ecommerce business.

Three customer categories:

  • VIP shopper – the most valuable customer giving most conversions.
  • Engaged shopper – visits often, an active cart and numerous product views. One or more conversions.
  • Window shopper – Several visits and many product views.

While you’ll naturally aim for VIPs, learning why those in the other categories are purchasing less often is vital. Are prices too high or are products unsuitable? Use a two-prong attack to get to the crux of the matter by combining data to see where you customer is turned off and communication through surveys to see exactly what’s going wrong. If needed, offer incentives for them to fill surveys and provide honest, valuable feedback - this can’t be overstated.

Prescriptive product and content placement

Buying behaviors change for many reasons. Seasonality and behavioral changes such as weather, stock shortages and promotions can all have an effect. Have a model in place to detect unusual conditions and be sure to adjust site merchandising to respond to these occasions. This could include changing the appearance of your home page so items that are likely to be popular are more prominent.

Also, consider the wider business. An increase in product supply is likely to have an effect on the wider business, so develop a strong supply chain to cope with demands. Your advertising budget may also need raising to cope with competition.

Improving personalisation

With communication becoming more segmented, it’s important to increase personalization to engage with a customer on a level that makes them feel appreciated while making the shopping experience unique to them. A business's potential customer base can be huge, but thanks to machine learning you can now segment customers into groups based on location, age or many other defining qualities to target your marketing more effectively.

What this means is those people that are affected by seasonality or behavioral changes, say, for example, businesses purchasing stock for winter or supplying items aimed at students can be targeted directly and you can plan accordingly for the potential uptick in sales that may result from your marketing campaign, bringing the whole process full circle.

Patch any holes

Last but not the least, make sure there aren’t any obstacles for people willing to buy your product or service. You can have the best analytics, feeding info to the top class marketing department, which is making kick ass job at converting visitors to buyers, only to have your unresponsive site turn them away from the purchase. Make sure everything looks and performs as it should, at any hour, from any region. Hire outside testers, if need be. If a certain item is out of stock, for example, make sure that reflects on your site immediately, and offer a replacement option in the meantime. At this day and age where people have loads of options, even such a “trivial” thing as loading time can greatly affect your business, as we can see clearly here. And finally, security. If a word gets out that customer’s accounts or funds are in jeopardy, that can cause irreparable damage to your profits and reputation. Hence, don’t skip on developing systems that will keep everything tight and secure. Things to look into include Django authentication for user logins, encryption for personal information, automated backups, and several options for account restoration, to name a few.

These are some things to keep in mind when entering the battlefield known as the e-commerce market of the 21st century. Cover these basics, and you’ll be well on your way to 5-star reviews. People often stay loyal to companies that provide excellent customer experience, not those that offer a necessarily better product, so play your cards right.

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