Cassandra Brighter· Author
With more and more product recommendation engines in the market, ecommerce sites continue to adopt this feature. We conducted a survey of 1,000 online shoppers to find how consumers feel about personalized product recommendations, and how these impact their decisions.
Sentiment Around Personalized Recommendations
Our data shows positive response is quite high. Only 12% responded negatively, finding recommendations “distracting.” In contrast, nearly ¾ of all shoppers found recommendations helpful:
– 72% of users feel positively about them.
– 12% find them distracting.
– The remaining 12% remain neutral.
Some of these differences can be attributed to how a product recommendation software is implemented, leading to a poor customer experience. Make sure to account for where a shopper is in your sales funnel, in addition to ensuring your tech stack is properly showing relevant product recommendations.
Age and its Impact on Product Recommendations
Age demographics play a crucial role:
– 41% of those aged 18-29 actively seek out product recommendations.
– Only 27% of individuals aged 65 and above do the same.
Younger generations have embraced AI-driven recommendations, and expect a collaborative, conversational experience on a page. It might be that older users have a more self-reliant mindset, expecting static pages. In the case of this demographic, product recommendations may suffer “banner blindness,” as older consumers seem to react to them the way they’d react to an ad.
Conversion Rates and Age Dynamics
– A staggering 79% of the younger demographic (18-29 years) responded they have purchased a product based on product recommendations.
– In contrast, 61% of individuals aged 65+ are influenced similarly.
This data reinforces the role age plays in online shopping behaviors and the weight these recommendations carry for different age groups.
The Influence of Product Recommendations on Additional Purchases
– 88% of respondents claim that product recommendations don’t influence them to buy additional items.
– Only 12% felt swayed by these suggestions.
Gender Dynamics in Product Recommendations
Gender also plays a role in how recommendations are received. Women are more likely to make purchases based on product recommendations (72%). In contrast, 62% of men are so influenced.
How Often Do Recommendations Lead to Purchases?
– 51% of users claim recommendations often leads them to buy a new product.
– 19% feel that they have led to a purchase at least once.
– 30% assert they’ve never been influenced by these recommendations.
Our 9 Recommendations for Your Product Recommendations
- Use Real-Time Data: Leveraging real-time data, as “Buy Buy Baby” does, helps in suggesting products based on in-session shopping behavior.
- Demographic-Based Recommendations: Target.com uses demographic data effectively, presenting categories and products most relevant to its users.
- Mix Similar and Complementary Products: Diversifying the type of recommendations, from similar products to complementary ones, can cater to a broader range of customer needs.
- Maintain Transparency: If collecting user data, ensure that privacy is respected, and consumers are aware.
- Harness Engagement Data: Andy & Evan, an American children’s clothing brand, saw a 50% increase in engagement by showcasing product recommendations.
- Increase Time Spent: Shoppers who engage with product recommendations spend considerably more time on-site, enhancing the likelihood of conversion.
- Leverage Past Purchases: Using purchase history can make recommendations more precise.
- Personalize Across All Platforms: Ensure a seamless experience across desktop, mobile, and even email marketing.
- Use Affinity Data: Like “Buy Buy Baby”, employ real-time affinity data to suggest products.
5 Critical Mistakes in Product Recommendations
- Overwhelming Users: Too many suggestions can be counterproductive.
- Irrelevant Recommendations: Offering unrelated products can alienate shoppers.
- Static Algorithms: The market is dynamic. So should the algorithms behind recommendations.
- Not Testing Regularly: Regular A/B testing ensures that the recommendations remain effective.
- Ignoring Feedback: Constantly refine recommendations based on user feedback.
Learn About Your Customers
In the rapidly evolving e-commerce landscape, understanding and catering to customer needs is paramount. It’s not merely about implementing recommendations; it’s about ensuring they are accurate, relevant, and genuinely beneficial to the shopper. To deepen this understanding, regularly employ customer insights, conduct surveys, and engage in direct feedback. By centering strategies around the customer, ecommerce platforms stand to reap tangible benefits in the form of engagement, loyalty, and increased sales.
Every feature you implement should be driven by customer experience. Once you implement a new feature, customer surveys can tell you in concrete, quantifiable ways whether the feature is well received, and whether it has improved customer sentiment and net promoter score.