Crank Up Your Ecommerce Search With Day Zero Learnings

Kait Spong
Kait Spong
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In the fast-paced world of ecommerce, it’s essential for online stores to provide a seamless and efficient search experience for their customers. A well-designed ecommerce search engine not only helps users find the products they’re looking for, but also significantly impacts an ecommerce site’s revenue. The importance of ecommerce search cannot be overstated.

An effective ecommerce search engine should be able to process complex search queries, understand natural language processing, and deliver relevant results based on search terms. By implementing AI-powered site search solutions and machine learning technologies, online stores can ensure that their customers receive the most accurate and relevant search results, enhancing their overall shopping experience.

Ecommerce sites must consider the power of natural language processing (NLP) in improving their site search functionality. NLP enables ecommerce search engines to understand and interpret user searches more effectively, even when they include colloquial language or misspellings. By leveraging NLP, online stores can provide a more intuitive and human-like search experience that better understands customers’ needs and preferences.

Furthermore, ecommerce personalization is an essential aspect of enhancing the search experience for ecommerce shoppers. By analyzing users’ past behavior and preferences, ecommerce search solutions can deliver tailored results that are more likely to resonate with individual customers. This level of personalization not only improves the customer experience but also increases the chances of converting searches into sales.

The Departure Point

Some people love a good road trip. For them, the whole point isn’t the destination — it’s the journey. Others don’t want to or can’t afford to take the time and enjoy the ride, and it’s more about speed and expediency.

It’s like the modern business landscape. Many companies simply (and quite understandably) don’t have the convenience to wait around for the final payoff — they need results now. Our advice? Let the Amazons and Metas of the world keep those garage and dorm room origin stories where there was no actionable plan to make a pipe dream into a real, revenue-generating business.

As a well-established brand that’s looking for what’s next, your commerce company is probably well beyond this point. You need speed to get you to the next phase of your business. So, you shouldn’t focus on the task of building your ecommerce search engine from scratch. 

Currently, commerce brands across multiple industries and markets have an eye on product search as their next ecommerce destination. Product search technology addresses poor search performance, removes strain from your team, and makes room for additional ecommerce initiatives as your business scales operations. However, search is a revenue stream that many brands continue to leave on “Empty.”

If you truly see your business as part of the customer-centric movement, you’ll need to eliminate search frustrations for your shoppers or buyers with the perfect vehicle to get them there: an intelligent ecommerce search engine. But in a market full of point solutions boasting the speediest uptime and the best results, how do you choose which ecommerce search tool is the right one for your team? 

Since implementation is complicated, expensive, and time-consuming, some solutions will tout time to implementation, but as a savvy ecommerce practitioner or leader, you’re likely looking for more concrete value, such as return on investment (ROI) and/or time to value (TTV). Now, you just have to convince your brand’s decision makers of the same

After all, wouldn’t your team rather do something right the first time, as opposed to doing it again down the road? If so, strap in for this road trip extravaganza with Bloomreach! We’ll show you the way as we make a few stops along the route to ecommerce success.

The “Black Box Roadside” Attraction

To break out of our ecommerce practitioner shell, we want to have some fun on this road trip and stop at some places we normally wouldn’t. Let’s start with a roadside attraction that piqued our interest when mapping out our route — the Black Box. In theory, the Black Box is the place to be. It promises to take the burden off of ecommerce professionals, allowing them to escape from the more mundane, repetitive tasks of their workdays. 

And yet, we find a lot of confusion around the behind-the-scenes aspect of the Black Box. It’s like the “Black Box Model” of computer engineering, which often faces a lot of critique in the tech community. While a black box is typically a system that can produce both useful information and extraordinary results for businesses, it’s often admonished for being unclear about its internal workings and having a general opaqueness surrounding its technology — whatever that might be.

What Are “Day Zero” Learnings? 

There are practitioners, engineers, and leaders out there, who would refer to an out-of-the-box ecommerce search engine as “too black box.” While we don’t consider ourselves as a black box at Bloomreach, we recognize that our solution is optimized with a bit of magic, aka the dataset that we’ve built over the past decade to best adapt to customer and buyer behavior. Bloomreach exists somewhere in the middle of the spectrum of “automated artificial intelligence (AI) solutions” and “self-service solutions.” This means that our self-learning site search engine is revved up from the start with numerous built-in capabilities, but it still leaves plenty of leeway for your team to scale and make decisions as they see fit. Think of our technology as a set of guard rails to help you maximize your business performance!

To some, especially a CTO or Head of IT, a pre-determined dataset seems a bit daunting because it’s unknown to them. But Bloomreach’s dataset, which we refer to as Day Zero Learnings, means that you’ll see an immediate impact on the quality of your search relevance (and in turn, ROI) since you don’t have to wait for a pixel to learn from consumers’ behavior first. You also don’t have to put the added, and often, confusing, workload of diagnosing and testing manual rules on your merchandisers. Our search engine is smarter today — even before we put it on your website — compared to other ecommerce search solutions on the market that need time to adjust and learn. With one of these tools, your website could look like this on launch day:

Ecommerce Search Needs AI: A Look Inside the Box

Now, let’s get back to that very “mysterious” black box. In reality, Bloomreach does not consider itself to be secretive or sneaky about our AI. Why would we be? We know that our product is a customer-focused solution that will give your brand the speed it needs to address your issues with ecommerce search from day zero. With that being said, we want to take a moment to show you what’s inside this so-called “AI black box” and how its components can provide the automation your team needs, as soon as our Discovery solution is fully implemented: 

Query-driven RPV

Most search engines are designed to improve either conversions or revenue. Only Bloomreach is optimized for query-level revenue per visitor (RPV). Our technology evaluates each searcher’s intent at the most granular level, showcasing the products they’re most likely to buy first with an emphasis on the items that will make the most revenue for the business. Remember, this happens from day zero, and as our search engine works with your brand, we continually optimize our ranking algorithm based on your customer or buyer’s behavior.

Semantic Understanding

Contextual knowledge is extremely valuable when you’re having an in-person conversation with someone. Your tone, delivery, and body language all convey meaning to the person on the other end of the exchange. But search bars on ecommerce sites often miss out on the nuances of human speech. Thankfully, our AI will allow your search bar to decipher your products on a deeper level and present them in ways that make sense to your customer. This is called “semantic understanding.” Bloomreach’s search engine deeply understands both customer intent and product attributes, so we know that vanilla can be a color, an ingredient, or a scent. Our technology automatically turns this understanding into relevant results at the search query level.

Extensive Synonym Database

Bloomreach has aggregated product searches from our huge list of customers over the past decade, which impacts the equivalent of over 25% of B2C ecommerce in the US and UK markets combined — second only to Amazon. We didn’t just arrive here, either. Our technology puts in the work and has the mileage to prove it, focusing on our clients’ customers and buyers every step of the way. In this time, we’ve also learned the most common synonyms (and even those pesky misspellings — hey, it happens to the best of us!) for nearly every industry. Luckily for our customers, they collectively benefit from these shared learnings, which only become more precise as our pixel continues to learn on your site and the many others we service across the globe.

Autosuggest

We’ve become accustomed to search bars assuming our intent with a drop-down of suggested search options. What we don’t realize, however, is that it can take search engines quite some time to get to this point of perfect prediction. With Bloomreach, autosuggest menus come to your brand out of the box and leverage our extensive synonym database to show your customers more relevant results at the search query level. Your customer or buyer will feel more understood by your website and be more likely to convert again and again (and again).

Smart Query Relaxation

Search results are everything to your customer or buyer. Too little, they’ll grow disinterested; too many, and they’ll feel overwhelmed. None at all? Well, you might as well just anticipate that they’ll bounce to your competitor at that point. If your catalog doesn’t have the exact product a customer is seeking via search query, then Bloomreach will increase recall in a way that provides results, yet keeps customer intent at the forefront. This facet of our AI leverages the same query-level semantic understanding, grasping exactly which attribute to relax — be it specific brand, color, or cut type — to show more relevant results, as opposed to a page of null results.

Bloomreach’s Net Promoter Score (NPS) is another indicator of our tool’s well-developed AI capabilities and successful integration processes. Over the years, we’ve undergone implementations so many times and know what to expect. To make your experience as pleasant as possible, Bloomreach leverages a team of product experts and former practitioners, who can teach your team how to truly leverage our ecommerce search tool and ensure that you’re set up for long-term success. Now that’s the kind of speed that really matters and is truly impactful.

The Next Stop on Your Ecommerce Product Search Journey

The Peak of the Digital Maturity Curve

As you’re leaving the black box roadside attraction, you’ll most likely feel some sense of relief. You’ve now nailed down a better understanding of Bloomreach’s AI. Since you have a more clear-cut understanding of what our AI does, you might be wondering what it looks like in comparison to other ecommerce search engines on the market. 

How convenient is it that our next stop on this eye-opening road trip happens to be the digital maturity curve? Not familiar with the concept? Let us chauffeur you up the long, winding road to the peak and show you all the various phases of AI maturity along the way! Afterward, we hope you’ll better understand where your business should start its product discovery efforts. (Spoiler alert: It definitely shouldn’t be Phase 0 — or even 1 or 2, which is where many of our competitors like to park.)

Before we get started on our ascent, we should take a look under the hood of our ecommerce search engine to make sure that everything is working properly.

One of the questions you might be asking yourself right now is: Does your current or prospective product search vendor align with your business goals? While offering search on your ecommerce website is now the industry standard, the way you lay out your search result, category, and product pages has a significant impact on key metrics in your ecommerce strategy and must be prioritized. We’re more than ready to take a deeper dive into the nuts and bolts, or the “engines,” of a relevant and personalized search experience.

Relevance

Your ecommerce team has a lot to consider daily. Not only do they need a deep knowledge of the products your business offers and their unique attributes, but they also have to organize all the data points from your customers to seamlessly bring them together. AI helps your search bar meaningfully understand your products and present them in ways that make sense to your customers or buyers. Then, the AI learns from consumer behavior to become smarter over time. This unique combination of natural language processing (NLP) and machine learning (ML) creates the semantic understanding we discussed earlier. It provides a relevance engine to customers who are tired of seeing irrelevant or null search results.

Optimization

Combined with the relevance engine of semantic search, an optimization engine will cut out unnecessary tasks, automate your ecommerce merchandising workflows, and result in a serious ROI. All the hours your merchandisers spend boosting and burying your products or creating synonyms for product attributes will be no more. An advanced ecommerce search solution can run in the background the entire time and significantly reduce redundant workflows — while still allowing merchandisers to intervene in the smart, strategic, and streamlined ways they see fit. Don’t forget that many solutions on the market require you to start from scratch and customize everything. Bloomreach provides you with the foundation, then empowers your teams to customize the last 10 to 20%.

Personalization

Irrelevant search results still plague customers today. Although many brands seek end-to-end, personalized experiences online, this promise remains unfulfilled, as personalization remains as elusive as ever. At Bloomreach, we believe that your brand’s search experience should be built for the customer’s or buyer’s motivations behind their purchase. This means, your search bar must fully grasp consumer intent and present all relevant options on the proper channels. This personalization engine will learn from user behavior and online interactions to continue creating granular 1:1 personalization at scale.

Customization

Ecommerce brands require an ecommerce search tool that can be customized to their goals. A good search tool is optimized out of the box, but will also improve over time based on insights from individual user preferences and site-wide product signals. That’s the beauty of Bloomreach — our customers don’t have to customize everything, and we believe that they shouldn’t have to do this to reach their goals. Top-notch product search technology must be designed to handle evolving traffic requirements, API callouts, and product catalogs. No matter what size your brand is or aspires to be, the technology underneath it all serves as the ultimate customization engine for your business needs. 

How Can Your Business Find a Place Along the Digital Maturity Curve?

We’ve said it before, and we’ll say it again: Ecommerce brands exist to meet the intent of the customer at any given moment, whether that moment occurs online or offline. These moments of intent can surface as the following:

  • Searching for a particular query
  • Expressing interest in a certain color (or another attribute type) based on a filter selection
  • Interacting with certain recommendations that your site generates

Every one of these instances presents an opportunity to connect with your customer in a meaningful way that encourages them to convert. A great ecommerce search engine should be able to respond and optimize towards intent to drive metrics, such as RPV, add-to-cart (ATC) rate, conversion, margin, and bounce rate.

Since you need AI to extract meaning from queries and separate products from their attributes, understanding customers through your search bar requires deep capabilities in NLP and ML. These algorithms work best when they’ve seen years of data to refine results and drive revenue, and many commerce brands (and even other product search vendors) lack this important intel to fuel their own product discovery solution. 

Believe it or not, there is a gold standard of site search, and every ecommerce organization — whether they’re aware of it or not — will find itself somewhere along the digital maturity curve. Now that we’ve explored the engines behind Bloomreach’s artificial intelligence, it’s time to take a journey to all the different landmarks (i.e. phases) of AI maturity before we reach the peak.

Phase 0 – Basic Relevance

Basic Relevance With Autosuggest, Facets, and Filters. Phase 0 is the starting point for the build-and-buy-its of ecommerce product search. If you begin at phase 0 of the digital maturity curve, your Engineering or IT team might have the intention to establish its own search engine. To do this, a combination of your internal teams would have to get data into the index, compile all product attributes, and build out basic facets and filters on your ecommerce website. Then, autosuggest would be hooked up to the browser, where it would learn from user behavior. Of course, like any good thing in life, this project will take a lot of time and dedication.

Phase 1 – Basic Algorithms  

Ranking Algorithms, Real-time User Signals, Stemming, and Synonyms. Now, let’s check out phase 1. Once your search engine grasps basic search relevance and begins compiling a list of product attributes, the tool’s focus can move beyond direct word matches and attempt to master word stems and synonyms. From there, the dynamic machine learning algorithms will continue to refine themselves based on data gathered from consumer actions across your entire website and beyond. Even though you’ll start to see more improvements here, it’s important to stay grounded in reality because ecommerce search is a long-term game of trial and error.

Basic Semantic Search With Ecommerce Merchandising Tools and Administration. As we move further up the digital maturity curve, your company will realize that the more mature the ecommerce search technology is, the more it will enable your business users to succeed without any help from IT. As your vehicle steadily makes its way up to the peak of the curve, you’ll progress from basic search relevance to basic semantic search. Now, the search technology will begin extracting meaning from queries and connecting them to the most relevant product descriptions. Keep in mind that any semantic engine is extremely complex and its early iterations will still be prone to missteps, unlike a solution that’s already well developed. 

Phase 3 – Advanced Algorithms

Advanced Algorithms and Semantic Search With Ontology and Inferred Attributes. Just like commerce-specific algorithms are important to solve specific queries for your shoppers and buyers, the relaxation of these same algorithms under the right conditions ensures that customers don’t experience that dreaded page of null search results. At this juncture of the road, we’re seeing the digital maturity curve expand and become even more advanced in semantic search. Since your data has to be rich enough to build ontologies and make inferences about product attributes at this leg of the trip, it can take brands years (and years) to find their way to this phase of the curve without help from an out-of-the-box ecommerce search solution.

Phase 4 – Advanced Personalization

Advanced Personalization and Merchandiser Analytics, Segmentation, and Custom Catalogs. You might feel excited (and maybe a little nervous) as you continue to climb to the top of the digital maturity curve. By the time your car reaches phase 4, you’ll start to see more possibilities over the horizon. Here, your solution will begin optimizing for the individual customer with 1:1 personalized product grids, more astute recommendations, and highly relevant banners. Your digital merchandisers can go beyond reactionary problem-solving at this point of the journey and become more proactive with your business data — taking profound, high-return risks based on the numbers and their human intuition.

Phase 5 – Advanced Search Intelligence

Advanced Synonym Detection, Automated Segmented Ranking, and Other Integrations. We’re almost there! More than ever, your team will see that customer behavioral data and machine learning lend a serious advantage to increasing revenue and reducing bounce rates. Advanced synonym detection, combined with the automated and segmented ranking from your marketing campaigns, will now allow your search engine to handle more complex use cases. Bloomreach is a prime example of this phase of AI maturity, with over a decade of synonym detection across a wide range of industries, from B2C categories (such as apparel and grocery) to B2B categories (like manufacturing and distribution). 

So, sit back and relax for the rest of the journey. Thanks to Bloomreach’s advanced placement on the digital maturity curve, your company can rest assured that every customer is treated like an individual from their first inquiry to the final transaction.

Your Ecommerce Team Is Almost There

The Last Pit Stop at A/B Test Café

You came, you saw, and hopefully soon, your brand will conquer your ecommerce strategy with an AI-driven product search solution. To show the endless possibilities of an ecommerce search engine that comes with day zero learnings, we want to make a final pit stop at the A/B Test Café. 

Serving Up 40+ A/B Tests Full of Ecommerce Search Wins

Known for its practical ingredients that make for a happy customer, the A/B Test Café has a trusted reputation among its patrons — or the B2B users of Bloomreach’s product search solution. To prove that we drive ROI, Bloomreach undergoes extensive, months-long A/B tests to prove it. Our users who expand across industries and markets have a proven track record of success with Bloomreach Discovery’s product search module (and other accompanying tools), as shown across 40+ of these A/B tests. 

The average revenue uplift in these A/B tests is 10% in search and 4% in category pages. These increases demonstrate that putting the right product in front of the right customer at the right time means positive business impact — and even a small improvement in site search goes a long way. Bloomreach succeeds every time because of our higher point of departure on the digital maturity curve. 

Reflecting on the different phases of the digital maturity curve, most of our competitors hang out around phases 0, 1, or 2, but you’ll find Bloomreach at the peak of phase 5 with advanced semantic search, personalization, and merchandiser analytics. A more developed search engine means more significant speed where itcounts.

Time to Implement vs. Time to Value: Which Is the Clear Choice? 

A few extra weeks of implementation time is worth the ROI you’ll experience sooner, with a solution like Bloomreach Discovery. While Bloomreach might not be the fastest tool on the market to implement, it boasts numerous benefits, including: 

  • Learned buying patterns from nearly every industry in ecommerce
  • A healthy balance of AI-driven automation and manual merchandiser control
  • Adaptable algorithms with configurations that you can control alongside Bloomreach’s AI
  • Tons of expertise from our business services team to help you identify new opportunities 
  • And, of course, fasterand more significant ROI than our competition 

Some solutions might take 3 to 5 weeks to stand up, but what’s next? While the standard Bloomreach implementation ranges from 6 to 12 weeks, our team of experts leaves you with a significant amount of material value throughout the onboarding process, along with continued relevance tuning, algorithm learning, and various ways to keep improving your commerce brand’s bottom line. What is the point of investing in a solution that trims off excess implementation time if you aren’t getting the results your business wants (and deserves) after making such a large investment?

Sure, starting with something is better than nothing, but this isn’t the case with product search. Your brand needs to combine the human expertise of your merchandising professionals with well-developed AI to truly build out an effective ecommerce search and merchandising strategy. Here are a few customer samples before ordering our entrée:

Welcome to Your Final Destination: Better Ecommerce Search 

In summary, ecommerce site search plays a pivotal role in ensuring an online store’s success by providing customers with an efficient and enjoyable shopping experience. A well-designed site search, powered by advanced search engines, not only improves the functionality of an ecommerce website but also contributes to higher conversion rates and customer satisfaction.

As you evaluate your ecommerce site search solution options, consider the importance of user-friendly search bars, accurate search results, and responsive search boxes that cater to various devices. By implementing cutting-edge search technologies and constantly refining your search function, you can create a seamless and engaging shopping experience for your customers, ultimately driving growth and success for your ecommerce business. As the world of ecommerce continues to evolve, staying up-to-date with the latest advancements in site search solutions will help ensure your online store remains competitive and customer-centric.

Reaching the end of a road trip can be a bittersweet feeling, especially when you’ve hit all the meaningful and memorable stops we have along the way. From our starting point — where perhaps, you were feeling a bit isolated in your typical ecommerce strategy — we took you to the black box roadside attraction where you learned more about the advanced AI beneath Bloomreach’s product search solution. Then, we drove you to the peak of the digital maturity curve and its many phases of AI maturity.

After learning about all of the different parts of Bloomreach’s ecommerce search engine, we concluded our journey at the A/B Test Café — the perfect place to stop, reflect, and sample all of the great customer stories where product search served up serious results for commerce brands across industries and markets. 

So, how do you get started with a solution as complex as Bloomreach Discovery? We suggest taking it for a test drive yourself. Learn more about our Search Impact Validation program, which allows practitioners to plug their unique product data into Bloomreach’s game-changing site search solution. Once all is said and done, we’re looking forward to getting you to your final destination! 

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Kait Spong

Senior Content Marketing Manager
Kait is a Senior Content Marketing Manager, specifically focusing on Bloomreach Discovery (search, merchandising, recommendations, and SEO), as well as the B2B market.

With eight years of experience in B2B SaaS, Kait remains passionate about delving into the technology solutions that improve a business’ end goals. Once earning their BA and MA in English, the seasoned writer delved into the world of content marketing, branding, search engine optimization, and social media marketing, helping numerous companies across all industries with their content and thought leadership strategies. 

What I love to do:

Making ecommerce technology easier to understand and more approachable for non-techies

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