Imagine an online retailer aiming to promote sales-boosting products, while embracing automation to provide personalized customer experiences.
This is exactly what deep merchandising can do in a product recommendations engine. This targeted approach while satisfying customers with personalized suggestions is crucial for businesses that rely on certain products for increased revenue.
According to a recent report, personalized product recommendations contribute to almost 31% of eCommerce revenues. You can be assured of getting a similar or more contribution in revenue with deep merchandising as it can promote products of your choice without compromising on personalized suggestions.
This ability to blend control over product selection with personalized recommendations has made deep merchandising a critical component of successful recommendation engines.
How Deep Merchandising Helps in Recommending Personalized Products
Deep merchandising allows you to fine-tune your product recommendations by setting rules and priorities that align with your goals. Whether it's promoting high-margin items, excluding low-margin products, or ensuring brand consistency, you can modify the personalized product recommendations accordingly.
Deep merchandising also leverages AI-driven algorithms that will continuously provide you with information to optimize your recommendations based on customer behavior. It gives businesses the power to intervene manually and adjust the recommendations to meet specific requirements.
Here’s how deep merchandising contributes to personalized product recommendations.
1. Balancing Automation and Manual Controls
Businesses can get the most out of a product recommendations engine with deep merchandising as it gives you complete control over whether to use manual or automated controls.
For instance, a company wants to suggest products from only specific high-margin brands. They can manually set custom rules such as product weight, height, or price to filter products and recommend them to the customers. Automated controls like AI ensure that the filtered products align with the business objectives by analyzing customer preferences, browsing behavior, and purchase history to provide tailored product suggestions.
This allows businesses to provide personalized customer experience while increasing revenue. It benefits businesses with,
- Increased Control: Ensures manual intervention without disturbing AI’s recommendation accuracy.
- Improved Customer Experience: Providing a personalized customer experience that aligns with business objectives.
- Business Performance Boost: Targeting high-margin products for recommendation will help to improve a company’s bottom line.
Consider the use case of a large electronics retailer. He can use deep merchandising to set rules to promote a newly launched high-tech device, while automation helps to suggest this product to the right audience by continuously analyzing customer behavior.
2. Product Prioritization for Personalized Experience
Companies often want to promote certain products—such as high-margin items or featured brands, because these align better with their financial or marketing strategies. However, there’s a risk that AI algorithms may not prioritize these products.
You can instruct AI algorithms to prioritize such products by feeding them with a set of rules. Through product prioritization rules, businesses can decide which products take precedence in their recommendations, while still allowing the AI to adjust and personalize for each user. This strategy helps the businesses with,
- Increased Revenue: The high-margin product prioritization helps businesses to improve their profitability.
- Enhanced Brand Visibility: Businesses can increase their brand awareness and exposure by featuring specific brands or products
- Improved Customer Satisfaction: Most of these recommendations will be new and valuable and can foster customer loyalty and satisfaction.
For example, a retailer can boost recommendations for specific brands during a promotion, ensuring those items appear higher in the suggestion list without completely overriding the personalized product recommendations nature.
3. Product Alignment for Business Enhancement
Deep merchandising not only can be used for promoting high-margin products but also for avoiding low-margin or out-of-season products from popping up as recommendations. Businesses can create rules based on product attributes, such as price, availability, or category to exclude certain products from recommendations.
For example, an eCommerce store might want to prevent recommendations of outdated products or those that are not in season, ensuring that customers see the most relevant and profitable items. This helps the brands to,
- Improve Brand Image: Avoiding irrelevant products from recommendations will help you maintain a positive brand image.
- Enhance Customer Satisfaction: As the recommendations are more relevant and timely, there will be ensured customer satisfaction.
- Increase Efficiency: The exclusion of irrelevant products can help businesses to streamline their operations and cut costs.
For instance, consider a sports retailer who doesn’t need to promote summer goods during the winter season. He can use deep merchandising to avoid such products and recommend only products with the product tag ‘winter’.
Bottom Line
Deep merchandising is one of the powerful ways to drive revenue while enhancing customer satisfaction. But to harness the full potential of deep merchandising, you should follow some best practices.
While deep merchandising allows manual control, it is essential to trust and let the AI do its work in the product recommendations engine. Overloading the system with too many manual rules can undermine the effectiveness of AI, resulting in a less optimal customer experience.
In addition, setting clear objectives before applying any rules, limiting restrictions on what products can or cannot be recommended, and making continuous adjustments can help businesses blend their objectives with AI. This not only improves customer engagement but also drives higher conversions and long-term business success.
