Personalization is the key to selling online. Without customization, you rely on consumers to find out what they want. By presenting relevant products, you eliminate all that hard work, which most buyers will not do anyway.
A Salesforce study conducted from March to June 2017 found that shoppers motivated by product recommendations accounted for 26% of revenue from e-commerce sites. This, despite results showing that only 7% of visitors click on such links.
The Salesforce study breakdown shows impressive details about the conversion rate, the rate of addition to the cart, the revenue sharing and the overall average value of the orders. Each device type recorded an increase in conversions and revenue.
|Conversion Rates||Register||Income Share|
|All Peripherals||4.6 times higher||24% higher||26%||] 10.3% higher|
|Desktop Computers||4.3 times higher||22% higher||25%||10.2% higher|
|Smartphones||4.3 times higher||26% higher||26%||7.9% higher|
|Tablets||4.1 times higher||31% higher||33%||15.2% higher|
Relevant recommendations can also help selling large banknotes. Last year, AutoLoop, which provides marketing services to auto dealerships, has put together a tool that recommends the best replacement vehicle based on someone 's purchase history. one, current monthly payments and other data. Consumers can restrict options by providing additional information.
Studies consistently show that product recommendations based on the interests or actions of a buyer stimulate sales. While most store owners and managers are aware of the importance of presenting this ideal content, most do nothing to use customer data to their advantage.
Getting started with product recommendations requires a plan of action. It should look like this:
1. Collect and compile data. If you do not have a big budget, start with Google Analytics and your shopping cart. Work on setting up third-party tools that collect other types of data, such as the level of scrolling of the page and the content with which they interact on social networks, including pages that qu & # # # They like on Facebook.
2. Decipher the data and deliver the content. For returning visitors, relying on historical orders and actions is a good way to make recommendations. For new visitors, use the most popular products and categories. Working with real-time data is also essential. This can be as simple as inserting conditions that display varying content, depending on where the buyer comes from – another website or social channel, for example. Or, it can be as complex as, for example, posting new ski jackets because it's just snowed Plattsburgh, NY and the customer – a long-time customer – lives 10 miles away and, according to your records, did not buy new ski equipment in two years.
3. Study the results. By tagging page elements and campaigns, you can track what works and what does not. This will increase conversions and order values for all types of buyers and product lines. Do not just look at the overall numbers. The study of segments and individual campaigns helps to find the weak links that lower the averages.
4. Take appropriate measures. You may be tempted to abandon all campaigns that do not work well. Many times, however, similar sites have the same problem. Concentrate on improving even the small things because they could ultimately have a huge impact.
Chances are, you will not be able to do all this yourself. Even if you are armed with this knowledge, custom script maintenance takes time. Consider a third party provider. Research before signing long-term contracts. Make sure the tools you use are secure, frequently maintained and accurate.