How to improve your marketing efforts with personalised product recommendations?
Product recommendation is an age-old marketing tool that has increased conversion rates by up to 915 per cent. More skilled marketers and merchants throughout the world, on the other hand, have gone beyond just recommending products. Nowadays, online retailers have transitioned from product suggestions to more personal data-driven recommendations to present the most relevant goods that consumers are interested in purchasing. And, as a result of these tailored data-driven recommendations, online retailers’ sales have increased by up to 75%.
However, given the enormity of data, ensuring that you capture all of the essential information and use it to your benefit may be a difficult job. Some merchants may struggle with the intricacy of product recommendations and ensuring that they are personalised to each customer’s visit. So, how can you expand your knowledge and insights about your consumers to develop a tailored interaction that drives conversion and revenue? Well, here are some tips to improve your marketing efforts with personalised product recommendations. So, let’s get started:
What are personalised product recommendations?
A tailored site product recommendation is not based on a guess or assumption. User activity is used to generate personalised suggestions. These goods have frequently been viewed, considered, or purchased in conjunction with the one the client is presently considering. You’ve most likely seen these suggestions on Amazon. They show right beneath each product description and are based on what previous customers bought.
Amazon has long been a master at personalised product recommendations. In fact, product suggestions account for 35% of the eCommerce behemoth’s revenues. Another mind-boggling statistic: Netflix generates 75% of its revenue by suggesting movies and series to its users. That’s terrific! If you haven’t taken product recommendations seriously yet, you’re throwing money away. Personalised product recommendations don’t stop at “what a customer might enjoy” and “what other customers watched”.
You can offer suggestions to consumers based on the following criteria:
- Best-selling items
- Frequently purchased together (complementary products)
- Products that are currently popular
- Featured items
- Products with the most views
Tips to boost your marketing efforts with personalised product recommendations:
- Make use of personalised emails and product catalogues:
Segmentation is critical for delivering relevant material. New subscribers should be engaged in a welcome programme automatically. Welcome emails increase income by 320 per cent when compared to a generic campaign. As part of this, introduce them to your best-sellers. Product recommendation in an email is the quickest method to get them interested in your product catalogue.
Make your audience sit up and give heed by displaying your product selection with category suggestions. Furthermore, AI-powered technology handles tag generation, so each block is automatically completed for you. You’ll also be collecting actual, essential data for your AI-driven product suggestion engine to utilise in the future by watching what they click and where they go.
- Mix and match product recommendations:
Often, the best strategy is to mix and match different sorts of recommendations. For example, if a known visitor comes to your homepage, you may want to make their buying experience more convenient. They might be seeking new items or wish to resume where they left off. You don’t know what the consumer is looking for because they haven’t yet clicked through to a category or product page. However, past browsing history and crowdsourced behavioural data might provide a fair idea of their requirements and preferences.
Combine individualised product recommendations with popular goods from their preferred category. In this manner, you may cover things they’ve already seen as well as those they may not be aware of. Changing things around also helps you avoid the dangers of over-personalisation. The same reasoning holds true for browse abandonment emails, where you may promote recently viewed products as well as popular alternatives.
- Use filtering based on real-time data:
Product suggestions, whether on your website or in marketing emails, have a great potential to increase sales. You don’t want to squander this valuable real estate on unnecessary or annoying product recommendations.
Price-based filtering of product recommendations is one approach. For example, if some of your clients fit the ‘bargain hunter’ character, you may display them less expensive product recommendations. This prevents scaring customers away with proposals that are out of their price range.
Also, it’s a good idea to provide product suggestions based on a customer’s previous browsing and purchasing habits. However, there are specific situations where it is inappropriate to promote a product that someone has already purchased. Some items, for example, are essentially one-time purchases. Excluding recent purchases from suggestions is far more beneficial for goods like these. Instead, businesses should concentrate on goods that add value to the initial purchase.
- Use location-based personalization:
Recommendations based on a customer’s behaviour are more likely to be valuable and relevant. Suggestions become much more potent when combined with location-based personalisation. The most recent marketing technology allows you to link a person’s geolocation to store and product location data. This means you may filter product suggestions so that individual consumers only see goods that are available near them – either in their area or at the shop nearest to them.
A retailer with several physical locations might display goods that are available at the shopper’s nearest location. This is an excellent strategy if your consumers want to click-and-collect or explore online before purchasing in-store. It’s also ideal for niche goods like career or event listings.
38 per cent of online shoppers indicated they would discontinue doing business with a company that offered bad product suggestions. Today’s shoppers want a personalised, one-of-a-kind experience. Basic recommendations, such as comparable goods and blockbusters, are simply no longer sufficient. If you own an eCommerce business, you must employ some form of customised product suggestions. However, if you depend just on generic ideas for comparable items, you may be losing out on considerable revenue.