Maximize Your Online Merchandising: Unify Search and Product Recommendations

Maximize Your Online Merchandising: Unify Search and Product Recommendations

September 6, 2022
InSearch
Team Streamoid

Even before the global pandemic, the number of customers starting their buying journey online was massive and now the numbers are much higher. Given these overwhelming numbers, brands need to make sure to appeal to their customers and target audiences in the competitive and cluttered market. Effective online merchandising enables brands to stand out and attract the right audiences to bolster sales and revenues.  

An effective strategy to maximize online merchandising is through the unification of search and product recommendations. Keep reading to find out how.  

Understanding Online Merchandising

Online merchandising/ e-commerce merchandising is the strategic selection, placement and presentation of products, product content, collections and promotions to optimize screen real estate and boost sales. Screen real estate includes all areas of the e-commerce website, app, e-commerce platforms, etc. where product content is displayed including product pages, category pages, search result pages, recommendations, ads and so on.  

Simply put, online merchandising is all about how businesses promote and sell products on their e-commerce sites to their customers. The goal of online merchandising is to help businesses to make the right products discoverable to the right customers at the right time, getting the customer to ‘add to cart’ and buy the product. To this end, brands monitor customer behaviour throughout their journey and apply online merchandising strategies to coax customers into making the purchase.  

The following e-commerce merchandising elements need to be continuously sharpened for better outcomes:  

  • Design – aesthetics and clarity  
  • Branding and storytelling  
  • Customer experiences  
  • Product descriptions and tags  
  • Product placements/ display  
  • Pricing  
  • Promotions for upselling and cross-selling
  • Mobile responsiveness  
  • Product images  
  • Shopping methods  
  • User generated content, etc.  

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Why is Online Merchandising Necessary?

There is fierce competition in the market and the customer attention spans are shrinking. Firstly, online merchandising enables brands to effectively manage their screen estate and show the right products to the right customers at the right time.  

Given the shrinking customer attention span, they have to get the customer interested within 8 seconds or the customer will bounce off to a competitor website. Effective online merchandising strategies and methods enable brands to spark interest in different products through intentional product displays, compelling storytelling, online visual merchandising, etc.  

Online visual merchandising is the process of crafting and enhancing overall customer experiences through the use of a range of visual elements such as compelling homepage storytelling, stunning product images, clean and aesthetic design, rich product descriptions, user generated content (feedback, reviews), etc.  

Effective online merchandising strategies also guide customers through search, product discovery, right up to purchase. They help brands to improve conversions, customer experiences and average customer lifetime value.  

The Latest Needs and Trends in E-Commerce Merchandizing

Minimizing Time & Efforts in Product Search and Purchase

One of the biggest trends in the recent years in e-commerce merchandising has been the consistent effort to create seamless site navigation and improving product searchability and discoverability. When customers are required to spend long minutes on endless scrolling to find products, there are higher chances of customer churn.  

The goal is to minimize the time, effort and hassle costs of customers in finding and purchasing products online. To this end, there is a need to create robust site navigation for visitors with rich, succinct and compelling content that magnetizes them. Site navigation must be consistent and properly categorized with suitable navigation titles and clickable links for each navigation element.  

Further, the product search features on the website must be intelligent, advanced and robust. Data suggests that e-commerce retailers investing in advanced search capabilities enjoy 50% higher conversion rates in comparison to those with basic search features. Moving forward, brands need to invest in advanced search features such as intelligent filtering, personalization, product recommendations and so on.  

Creating Omnichannel Experiences

74% of online shoppers take advantage of multiple channels to search products and complete transactions during their purchase journey. Another statistic suggests that the shoppers using multiple channels for online shopping purchase 3 times more than shoppers using single channels. 75% customers expect unified experiences across all or any shopping channels they choose.  

So, brands must have a presence beyond the confines of their eCommerce websites and apps; they need to be present in every touchpoint and channel that their customers and target audiences are on. Else, they will lose out to competition in the omnichannel eCommerce landscape.  

However, it is not enough that they keep adding newer sales channel. Doing so, without proper strategies and tools will only create broken user experiences. eCommerce brands need to build robust omnichannel strategies and ensure consistent, seamless and tailored customer experiences across the diverse sales channels and platforms.

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Personalization Beyond Simple Gender & Age-Based Recommendations

Another key trend in eCommerce merchandising is the growing levels of personalization. Data says that 80% of customers are more likely to purchase from brands that offer personalized experiences. There is a strong need to improve relevance for customers in their search and discovery.  

Brands cannot confine themselves to the simplistic gender-based and age-based recommendations alone for personalization. The entire shopping experience, right from discovery to purchase and beyond, needs to be personalized and tailored based on the individual customer needs, preferences and their current and past behaviours.  

With the personalization game rapidly advancing, forward-thinking brands are leveraging automated tools and self-learning AI to offer hyper-personalized shopping experiences. This way, the look and feel of the website/ shopfront differs across different customers. They get highly tailored, real-time recommendations and promotional offers.

Leveraging AI, ML And Analytics for Agility, Accuracy and Efficiency

There is a strong need for agility, accuracy and efficiency in e-commerce. If brands are unable to respond and adapt quickly to the rapid changes in the market, they lose business. This is especially the case for microtrends wherein responding within 24 hours would also be late. As a result, it is imperative for brands to leverage AI, ML and analytics in e-commerce merchandising. Using these latest technologies, brands are also improving their accuracy and efficiency.  

Challenges Faced by Brands in Online Merchandising

  • With no physical stores, brands need to offer ways for customers to visualize products better. The use of technologies like AR visualization tools, style notes (for fashion products) and strong online visual merchandising measures help.  
  • Reliance on manual and traditional methods of merchandising which are arduous, time-consuming and wasteful.  
  • Collating massive volumes on product data and presenting them in an appealing manner. This is especially challenging when brands rely on manual or rudimentary merchandising methods.  
  • Challenges in adapting to omnichannel and offering consistent experiences across multiple channels.  
  • Achieving personalization at scale  

Unifying Search and Recommendation to Maximize Online Merchandising: How Does it Help?

They Serve Similar Goals

The recommendation engines analyse customer behaviour, their purchase history, etc. to learn their preferences and needs, accordingly, recommending products they may like. Search engines take user query information – the current purchase intention of the customer – to match and return relevant products.  

The common goal of search and recommendation is to help potential and existing consumers find products to purchase, even though recommender engines and site/ product search engines are used separately. By combining search and recommendations, brands can drive deeper engagement and better outcomes.  

There are several approaches to unifying search and recommendation systems. One is to build a system that combines a rich set of search and recommendation features using multinomial logistic regression model. Another approach is to use gradient boosted tree ranking models to integrate search and recommendations.  

The latest model explicitly predicts and models the user’s categorical choice and their purchase state (new purchase, repeat purchase, variety seeking, etc.). The insights offered through these kinds of models are beneficial in implementing highly targeted and personalized advertising and marketing campaigns to suit the needs, context and specific user-state, driving more purchases (especially repeat purchases).  

Enhances Product Discovery

eCommerce merchandizing Isn’t only about displaying products in an aesthetic and appealing manner. It is as much about optimizing the path to purchase, regardless of where the customer enters the website or which platform/ sales channel they are using or where they are in their buyer journey.  

By integrating product search and recommendation engines, eCommerce brands can significantly enhance product discovery. How so? Brands can go beyond simplistic and standard attributes such as colour, pattern and size to provide customers with a range of attributes that are important to them based on insights from real-time customer behaviour, search history, customer needs, preferences, etc.  

Brands can further use these insights, real-time user intent insights and search patterns to finetune recommendations, showing customers related/ complementary products, other products they may love, etc.  

Helps In Creating Personalized and Seamless Customer Experiences Online

Unifying search engines and recommendation systems empowers e-commerce brands to craft highly personalized and seamless online shopping experiences for their customers. Brands can leverage real-time insights from search to gauge customer intent, needs and unique preferences to offer relevant recommendations, personalized offers and discounts, tailor promotional and marketing messaging across different channels and so on.  

For instance, a customer is browsing through for oversized t-shirts on the website and then on a marketplace to compare prices. Using the insights on filters used, search history, etc., brands can show an ad or send an email to the customer with personalized offers. They could reflect these offers across the different touchpoints the customer may look for oversized t-shirts. In effect, they can convert their window shoppers into paying customers by personalizing the shopping experience.

Improves Relevance

By combining search and recommendation engines, brands can improve relevance and thereon boost conversions and revenues. When the unified system is equipped with the best-in-breed technology such as machine learning, AI, automation and analytics, brands can massively reduce the time and effort customers need to find relevant products.  

Increase Average Order Value  

Unifying search and recommendation enables brands to unlock a sea of opportunities to cross-sell, upsell and highlight promotional products. In addition to converting more window shoppers and browsers into paying customers, they can increase the average order value for each customer.  

Brands can highlight best-selling products, highly profitable items, highly searched items and so on. They can recommend related and complementary products, other times the customer may love, etc. They can also hide low-value, out-of-stock products to keep customers from detracting from other items. They can highlight personalized offers, discounts and promotions to boost conversions.  

Conclusion

Deepen customer engagement, boost revenues and maximize the ROI of online merchandising efforts by unifying search and product recommendations. Streamoid offers the most advanced domain-optimized search engine that combines product search and recommendations, tailored for the fashion industry. This is an end-to-end solution that enables brands to deliver rich shopping experiences through optimized online merchandising.  

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