For online shoppers, endless product choices have become the norm. But navigating overwhelming ecommerce catalogs often leads to analysis paralysis. That prevents customers from confidently selecting items that align with their needs.
Streamlining this experience requires a modern approach. That’s where ecommerce shopping assistants come in. These intuitive digital tools transform online shopping into a curated, personalized experience tailored to each buyer’s particular requirements and preferences.
In this guide, we’ll explore how to implement a best-in-class ecommerce shopping assistant to elevate the customer experience. Learn the benefits, strategies, and best practices for delivering tailored product guidance.
What is an Ecommerce Shopping Assistant?
An ecommerce shopping assistant is a digital tool that guides online shoppers through an interactive experience to recommend the most relevant products. Rather than overwhelming customers with endless search results, these assistants use data inputs like intended use, size requirements, style preferences, and more to curate a shortlist of best-matched items.
This is important to meet the demands of the way people shop online. Consumers don’t just prefer personalization, they expect it. Plus, they get frustrated when brands don’t deliver personalized interactions. And when buyers get personalized product recommendations, they’re more likely to make a purchase and to be repeat customers.
The assistant prompts users to share key criteria through simple questions on a product finder page or conversational chat interface. As you respond, the tool’s algorithms analyze the data to show product recommendations from the retailer’s full catalog. Each suggestion may showcase detailed specs, images, ratings, and the reasons why it meets specific needs.
These interactive assistants educate shoppers on which product features and attributes matter most for their particular use case. By delivering personalized, data-driven recommendations, virtual shopping assistants elevate the online buying experience and boost customer engagement.
How Shopping Assistants Are Different From Other Product Guidance Options
While the goal of simplifying product discovery is always the same, ecommerce shopping assistants take a unique approach. Here’s how they compare to other methods ecommerce businesses may consider.
Product Configurators and Customizers
Configuration tools allow customers to individually select and customize different product components or features for their preferences (like building a custom computer or car). While this functionality is effective for some goods, product configurators require upfront product knowledge from customers.
Shopping assistants are different because they gather information about the user’s needs first, starting at a basic level. Then, these assistants work to intelligently guide customers to pre-built product recommendations tailored to their inputs. This automated, personalized approach simplifies discovery for complex product sets.
Quizzes
Both shopping assistants and quizzes ask questions and generate recommendations based on the provided answers. A typical quiz will have a static series of questions and show customers a long list of pre-set results. In other words, there’s no true personalization—customers are stuck with the same results they’d get from basic filters or search tools.
On the other hand, ecommerce shopping assistants adapt to each customer. The order of questions and the number of questions can be modified based on the customer’s responses. The product recommendations are extremely specific and personalized. It’s possible that no two customers get the same combination recommendations. This is true personalization, which has been shown to greatly increase everything from conversion rates to revenue and customer satisfaction.
In-Store Sales Associates
For complex products, in-person staff can ask questions and make tailored recommendations similar to shopping assistants. However, associate guidance is manual, prone to inconsistency or bias, and doesn’t scale easily.
Digital assistants provide an always-available “virtual expert” that consistently guides with data-driven logic across all customer touchpoints. Conversational AI technology can also mimic aspects of interactions with an associate while capturing data.
Navigation and Filters
Offering basic search with filters (by price, brand, rating, etc.) is a must for any ecommerce site. But this can still overwhelm customers, who must navigate options themselves with limited guidance.
Well-designed assistants enhance search by first understanding unique customer needs by asking the right questions. Then, they use that context to instantly surface best-fit products for every shopper.
While product configurators, in-person expertise, and simple navigation fill important roles, ecommerce shopping assistants provide unique value. Their ability to deliver automated, individualized product recommendations tailored to each customer’s particular needs elevates the online shopping experience.
How Do Ecommerce Shopping Assistants Benefit Brands?
What do brands get out of implementing ecommerce shopping assistants on their sites? These are some of the benefits.
Higher Conversion Rates
Conversions are what keep businesses going. The average conversion rate in ecommerce increased by 10.32%, from 1.76% to 1.95% in March 2024 compared to March 2023. What can brands do if they aren’t seeing an increase?
By guiding customers to the most relevant products for their needs, shopping assistants reduce the barriers to purchase. This personalized guidance builds confidence, leading to more checkouts.
In fact, 45% of surveyed Millennials would like to have personalized products recommended when shopping online. Personalization also appealed to the same percentage of Gen Z online shoppers.
For example, a shopper looking for a new DSLR camera may feel overwhelmed by the number of models, lenses, and accessories. An ecommerce shopping assistant could ask about their photography experience level, typical subjects, and budget to curate a short list of products for their skills and interests. With a streamlined, needs-matched set of recommendations, the customer is far more likely to confidently make a purchase.
Boosted Average Order Values
Average order value is the average amount of money customers spend per transaction. It’s important to understand what the average order values are for your industry. This helps you understand if you’re keeping up with competitors and if there’s room for improvement.
For example, In March 2024, the AOV in the fashion and apparel space was $309. That’s more than double the average order value from the previous month. Implementing an eccommerce assistant can help brands reach or exceed numbers like this.
In addition to driving more purchases, assistants can showcase complementary items and up-sell/cross-sell opportunities based on crowd-sourced insights. This intelligent product bundling maximizes basket sizes.
Imagine that a shopper finding a new laptop can also receive recommended accessories like cases, chargers, or mice based on their needs. This intelligent upselling feels relevant rather than pushy. With combinations designed for each unique buyer, customers are more open to the chance to purchase perfectly matched bundles.
Decreased Product Returns
When asked about “Most returned online purchases by category“, most U.S. respondents pick “Clothing” as an answer. Ecommerce shopping assistants are particularly helpful in industries that have many returns. With smarter product matching, retailers see fewer returns and exchanges due to ill-fitting or incorrect orders.
How does this work? For example, an ecommerce shopping assistant can capture body measurements and fit preferences to identify outfits in the right sizes and cuts. Accurate sizing data can prevent those costly returns.
Invaluable Voice-of-Customer Data
Ecommerce shopping assistants also provide value beyond each sale. Every question customers answer provides behavioral data around their specific needs and preferences. This data can fuel marketing, merchandising, and new product decisions.
Scalable Product Expertise
For industries where sales are seasonal, ecommerece shopping assistants offer another benefit. Unlike training staff, AI assistants provide personalized guidance cost-effectively and consistently across all customer touchpoints, even during high-traffic periods. This expertise is infinitely scalable.
Better Brand Experiences
Most major brands have an online presence and ecommerce offerings. Individualized shopping journeys powered by eccommerce shopping assistants offer a competitive advantage. Brands can stand out with best-in-class digital guidance that increases customer satisfaction and loyalty.
How Do Ecommerce Shopping Assistants Help Customers?
Wondering what customers can expect after you implement this technology? Shopping assistants have become invaluable tools for enhancing the customer experience. These are some of the common benefits.
Simplified product discovery: Assistants streamline finding the right products. This real-time, personalized guidance avoids overwhelming shoppers with too many irrelevant options.
Education on product fit: Through a consultative experience, these tools highlight which product features and specs actually matter for the shopper’s specific use case.
Confidence in selections: Getting personalized product guidance from a shopping assistant helps customers feel confident that they’re buying the best solutions. This certainty drives conversions.
Faster paths to purchase: By efficiently bringing shoppers to the best items, assistants accelerate the buyer’s journey from discovery to purchase.
Ecommerce shopping assistants offer a win-win situation for brands and customers. Brands see more growth and sales success. Customers can find the items they need faster and benefit from a company’s products or services more quickly.
7 Examples of Ecommerce Shopping Assistants
Now you know the benefits of implementing ecommerce shopping assistants. What does this technology look like in practice? Take a closer look at these ecommerce shopping assistant examples.
1. GE Healthcare Contrast Media Smart Assistant
The Contrast Media Smart Assistant simplifies selecting the right contrast media for medical imaging. Answer a few questions about the imaging modality and the prescribing information needed. Users receive details, complete with detailed product information and administration guidance. This intuitive tool helps people choose media optimized for image quality, patient safety, and workflow efficiency.
2. Alen Digital Assistant
The Alen Digital Assistant guides users in finding the ideal air purifier for their indoor spaces. Simply input room dimensions, specific air quality concerns like allergies or odors, and feature preferences. From here, potential customers can browse top-rated Alen models recommended to effectively clean the air. Specific details about coverage areas, filter types, and smart features empower confident selections.
3. Ingersoll Rand Parts Finder Assistant
Quickly identify and purchase genuine Ingersoll Rand replacement parts with the Parts Finder Assistant. Customers enter the air compressor’s model information to explore compatible components across air ends, motors, coolers, and more. Detailed part specifications and descriptions ensure a match. This digital tool streamlines maintenance so customers can keep critical equipment running well.
4. Dick’s Running Shoe Assistant
The Running Shoe Assistant takes the guesswork out of finding properly fitted running footwear. Customers share details about their arch-type, typical runs, and their training schedule. Then, top recommendations across brands provide the cushioning, stability, and fit that customers need. User-friendly guidance highlights each shoe’s features to uncover the perfect pair for training.
5. Lucky Bike Accessories Assistant
Customers can easily upgrade or replace bike components with the Lucky Bike Accessories Assistant. After entering bike model information, they can see new saddles, handlebars, pedals, or other parts. From there, it’s easy to browse compatible options tailored to unique cycling needs.
6. Eppendorf Centrifuge Assistant
It’s simple to select the ideal centrifuge for lab applications using the Eppendorf Centrifuge Assistant. Specify type, speed, and capacity needs. Then, this tool will recommend centrifuges optimized for requirements across the available models.
7. Straumann Digital Assistant
The Straumann Digital Assistant streamlines purchasing dental materials. First, customers indicate the implant type they need to use. From there, it’s possible to browse tailored product recommendations complete with all relevant technical specifications.
Best Practices for Ecommerce Shopping Assistants
The most effective ecommerce shopping assistants follow certain best practices to drive results. Here are ten strategies to maximize the impact of this technology.
1. Ask the Right Questions
Gathering accurate data points on customer needs is critical. Prioritize questions that quickly identify the primary use case and preferences. From there, you can hone in on features/specs, and any other factors that determine product fit. The more details you get upfront, the better recommendations will be.
2. Educate Shoppers Along the Way
Asking the questions is just the first step. You can also use the flow as an opportunity to educate customers. Give them details about important product attributes and selection criteria. Explain why you’re asking certain questions and how the details provided will help find the best solution. This can help you build trust and authority.
3. Offer Relevant Product Recommendations
Once you’ve gathered input, make sure your shopping assistant is set up to surface a curated set of tailored product recommendations. It should satisfy the criteria provided and show the best possible recommendations. This requires you to have clean data and clear product descriptions that show the relevance to customers.
4. Provide Unbiased Guidance
While your goal is conversions, prioritize providing objective, needs-based product guidance. This will always be more important than steering a shopper toward any potential purchase. Position the assistant as an unbiased expert advisor focused on finding the best solutions in your catalog, not pushing certain inventory.
5. Integrate AI for Conversational Abilities
Artificial intelligence is used in retail companies around the world. Nearly 40% of retail directors stated they used artificial intelligence. Another 35% of respondents reported to have already scaled up this type of technology, while 15% of surveyed retail directors projected that it would be implemented within the next 12 months.
Try modern AI shopping assistants that use artificial intelligence, machine learning, and NLP for more conversational interactions. This flexible approach and options like chatbots allows shoppers to provide inputs more naturally. This way, the entire process feels as human and personalized as possible.
6. Incorporate Product Discovery Analytics
An effective assistant captures deep insights into how shoppers navigate their product finder experiences. This includes the features they value most, cart abandonment rates, and paths to purchase. Don’t ignore these product discovery analytics, Use them to optimize future shopping journeys and marketing strategies.
7. Keep Assistants Up-to-Date
Ensure your ecommerce assistant stays current by regularly auditing included products and incorporating new releases. Also, use your data-driven insights to identify emerging customer needs and continuously improve and expand question flows. This empowers you to evolve with changing trends and expectations in the market.
8. Educate Customers on the Benefits
Helping customers understand the value of ecommerce shopping assistants is key. Strategically highlight how these tools simplify product discovery across your marketing channels. Use blog posts, emails, and on-site banners to showcase the assistant’s ability to curate personalized recommendations. When customers understand the convenience and confidence assistants provide, they’ll be excited to engage.
9. Guide Users Through the Experience
Don’t assume customers instinctively know how to use shopping assistants. Provide clear instructions that walk them through the interactive process step-by-step. Include guidance directly into the on-site assistant flow itself. Prompting them on which information to include builds familiarity with the format. When you seamlessly onboard users, you make it more likely that they’ll become repeat users of the assistant.
10. Integrate Across Customer Touchpoints
Promote awareness and drive adoption across channels like social media, email, and SMS. By embedding the assistant into these other digital touchpoints, you increase exposure with customers at all stages of their journeys. This multichannel integration reinforces the tool as an always-accessible digital expert.
Understanding The Future of Intuitive Ecommerce Experiences
As customer expectations around personalization and convenience continue to rise, brands must prioritize implementing ecommerce shopping assistants. These intelligent product recommendation tools are no longer just nice to have. They’re essential for increasing conversions. Guiding customers to the perfect product every time is one powerful way to sell more.
By deploying an intuitive, best-in-class shopping assistant, brands elevate the entire online buying experience. You can streamline product discovery by gathering customer needs and preferences through conversational AI-powered interactions. Tailored product recommendations highlight the most relevant solutions across your catalog. Plus, insightful analytics capture customer data that your business may not otherwise have.
The result benefits everyone. Satisfied customers feel understood and confident in their tailored purchase journeys. Increased conversions as choice overwhelm disappears. Brands see stronger customer loyalty and a positive impact on their bottom line.
Looking for a way to implement product recommendations in your ecommerce store at scale? Check out a product discovery platform like Zoovu. Request a demo here.