According to the Personalization Pulse Check report from Accenture Interactive, 91% of consumers prefer to shop at stores that remember their shopping preferences and offer them personalized offers. The solution is to create very advanced personalization, which requires the acquisition of a large amount of customer data. Let’s look at how to personalize customer experience based on various events, such as current location, specific tastes, favorite communication channels, activity time and more.
Solution 1. Personalized recommendations
To increase customer interest, use product recommendations based on customer histories; what they buy, what they have recently viewed and which category of products they visit most often. This way, each customer will see their own version of the product page, with a personalized offer.
There are a few different ways to make recommendations, based on various algorithms:
Suggest products based on online browsing history
Display recommended products selected on the basis of similar browsing paths of other customers. As a result, users will see products they have browsed recently. They can work well in every industry because they remind customers of recently viewed products.
Suggest products based on similar online customer histories
The Machine Learning mechanism on the website will allow you to completely automate the process. As a result, users will see products that other, similar customers also liked or bought.
Suggest products based on a customer’s purchase history
You can offer similar products in terms of style, colors or categories, which is especially effective for fashion, cosmetics, jewelry, etc. However, this will not work in industries such as automotive or home electronics/home appliances. Offering products with a very long shelf life/use and requiring significant investment have a different customer path.
In this case, it is worth offering complementary products, such as car floor mats, dish washer cleaners, phone cases etc.
Display best-selling products (bestsellers)
The psychological mechanism of social proof causes the choices of other people to influence our final choice. It motivates customers to browse and often buy products that are popular. This mechanism can significantly increase the number of conversions. It’s particularly effective in fashion, shoes and home furnishings.
Knowledge about the customer's purchase history allows you to avoid annoying situations when they see promotional offers for a product that they have already bought.
Solution 2. Personalized website
83% of consumers are willing to share their data in order to receive personalized service. Taking this into account, website personalization is not just important, but essential. Elements of personalized websites you can use in your strategy:
Content can be changed based on client segments in the form or, for example, special offers for loyal customers, discounts for new clients, etc. You can also adjust them based on the customer behavior—banners presenting products from recently-viewed categories, complementary products etc.
Dynamic content in the basket
You can display selected creations matching the tastes of particular users. In this example, for women who love romance films, Netflix displayed a picture that can be associated with a romantic date. For people who prefer comedies, Netflix showed a shot with Robin Williams, who is well known to the audience mainly from comedy roles. Thanks to this, the message matches every user's preferences.
Solution 3. Personalized emails
- Welcoming new subscribers to newsletters
- Thanking customers for making a purchase
- Sending reminders about abandoned carts
- Discounts on recently viewed products
- Birthday wishes
Solution 4. Personalized price
Both time promotions and permanent discounts depend on the customer’s behavioral history. They also increase interest in your offer and generate more profits. Many of them can be automated, meaning you will be able to save time, and discounts and promotions will appear automatically when it is profitable and only to those clients who are actually willing to convert.
- For customers who are in your store for the first time, you can show a pop-up with a sign-up form. If they don’t fill it in the first time, you can display the pop-up twice, e.g. after adding a product to the shopping basket.
- You can also send special discounts to customers who have viewed products from a certain category several times but have not made a purchase.
- You are able to build transaction programs based on frequency, type and value of purchases as well as other events in the system.
Making a transaction via specific triggers (events that precede conversions), e.g. coupon downloads or newsletter subscriptions, results in adding scoring points. Based on these points, you can grant appropriate discounts to specific groups of clients according to their commitment.
- Divide your base into groups according to the likelihood of conversion in a given time period. Do not send discounts to those who are most active and likely to make a purchase, or to people who do not visit your site and are not interested in it.
Focus on intermediate groups, with purchasing potential, but requiring activation from your side.
Solution 5. Predict the future
Next Generation Marketing is based on Machine Learning mechanisms that analyze large data sets. Based on their analysis, you are able to identify groups of similar users that show certain patterns of behavior.
If a new user starts to behave according to a given pattern, the effect of their actions is very likely to be similar. All these formations change by themselves and are dynamic.
How to optimize campaign spending based on predictions
Group your database according to the probability of conversion or other activities. This enables you to direct your marketing message to those with a medium or low chance of converting.
By not directing discounts to those who will convert anyway or to those who are not interested at all, you will save on your advertising budget.
Personalize customer experience with confidence
Personalization lets you convince your audience that you are talking to each of them directly. It can help you boost their loyalty and encourage them to stay with your brand. By using the right tools and putting your customers first, you will enhance their satisfaction and decrease churn. And it is worth remembering that in terms of sales, lower churn might speak more about customer loyalty than increasing revenue.