On an e-commerce site, your whole product world should be designed for your customer. Merchandising has a strong impact on how users navigate through your site, and therefore on their purchase behaviour. Optimisation tactics vary from categorisation and choice of filters to how prices are displayed and the design of your pages. By keeping your online store ultra-organised, you’ll attract more customers, generate more conversions, and grow your average basket value. Here we’ll explore 4 visitor behaviours that can indicate whether your product catalogue is performing optimally.
Searching for products using your internal site search
27% of visitors to an e-commerce site start their visit with a search on the internal search tool, and 50% use the internal site search at least once during their purchase journey. Generally speaking, a visitor who uses your internal search engine is already beyond the discovery phase – he or she is looking for a specific product or service, and the probability that he/she purchases is therefore much higher.
Different data can help you evaluate how your internal search tool is performing:
- Rate of use:the percent of visitors who used the search feature
- Keywords entered:the keywords or expressions typed by your visitors
- Exits after search:the ratio of visitors who left your site immediately after their search
- Searches without results: the keywords entered that generated no results
Regarding this last point, it’s always helpful to know which keywords were searched to ensure that typos are not to blame when no results are returned. It’s also a way of verifying that your product offerings sufficiently match what your visitors expect and are seeking. If you sell mobile phones, for example, but not the accompanying accessories, most of your visitors might wind up frustrated. Analysing your internal search engine can help you be sure about what your customers are really looking for.
Clicking on suggested products
E-commerce sites have become increasingly refined over the last several years and now commonly feature suggested products directly in the internal search tool, in product listings, or on product pages. Here’s an example of product suggestions that appear in the search tool on www.bestbuy.com:
By measuring impressions of your suggested products and the number of clicks, you’ll quickly determine a click rate. With this metric, you can track how attractive your products are to visitors over time and understand how effective your merchandising is. You can also analyse how these product suggestions contribute to adds-to-cart and conversions by comparing the actions of visitors exposed to product suggestions to actions of non-exposed visitors. If a visitor sees a product suggestion, is he/she more likely to place that product in his/her cart and purchase it? Once you have the answer to this question, you can adjust your selection of suggested products to boost the performance of your product catalogue.
Reacting to flash sales and promos
A UK survey shows that up to half of consumers will only make an online purchase if the product is on sale or part of a special offer. You undoubtedly run promotional offers to boost your sales. But which products are most profitable to promote? By comparing a product’s average price with its total sales volume, you can determine whether a decrease in price can be sufficiently buffered by additional sales, or if dropping the price will reduce your margin. When consulting a multi-metric line chart comparing “Price/Sales” in your analytics solution, you may notice that certain products have significant elasticity, meaning a drop in price can strongly boost the volume of sales (more significantly than with other products). This analysis gives you immediate insights for your catalogue categories featuring promotions (coupons, promo codes, flash sales, special offers, annual sales, clearance, etc.).
Interacting with chatbots
Chat modules on e-commerce sites are a major trend. It’s estimated that chatbots will handle 85% of all customer service interactions by 2020 (and that the average Internet user will have more conversations with bots than with their significant other…).
The earliest virtual assistants left a lot to be desired. But today, they are well-integrated into sites and are triggered depending on navigational scenarios. If a visitor views a certain number of pages within the same category, or if he or she remains stuck without taking any action during a certain time frame, the chatbot will be triggered and a chat assistant will guide the visitor to the following step. When used well, chatbot tools can create many advantages: reduced costs, personalisation of the customer relationship, and better brand image.
To understand how your chatbot is contributing to conversion, create 3 segments amongst your audience, as in this example:
1) Visitors who did not interact with the live chat
2) Visitors who interacted for less than 5 minutes
3) Visitors who interacted for more than 5 minutes
|No live chat usage||136,210||3,909||2.87%|
|Conversation shorter than 5 min||23,449||694||2.96%|
|Conversation longer than 5 min||47,893||1,509||3.15%|
By carefully examining behaviours in each segment, you can evaluate your chatbot module’s impact on sales. When combined with other customer information and then analysed (product recommendations, stock or delivery information, customised or personalised ads), data from your chatbot is a powerful lever for improving customer satisfaction.
And with your e-commerce CMS (like PrestaShop for example), there are simple and quick ways to collect data and extract insights. Certain plugins can deploy and enable all features of your digital analytics solution on all your pages with just a few clicks.
With AT Internet, a plugin is available for the last two versions of PrestaShop (1.6 and 1.7). With this plugin, there’s no need to spend time integrating extra script into your pages, or to pay your agency to do it manually. Everything is automatic. (And other extensions for e-commerce CMS will soon be available as well.)
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