Search by Algolia
How to increase your ecommerce conversion rate in 2024
e-commerce

How to increase your ecommerce conversion rate in 2024

2%. That’s the average conversion rate for an online store. Unless you’re performing at Amazon’s promoted products ...

Vincent Caruana

Senior Digital Marketing Manager, SEO

How does a vector database work? A quick tutorial
ai

How does a vector database work? A quick tutorial

What’s a vector database? And how different is it than a regular-old traditional relational database? If you’re ...

Catherine Dee

Search and Discovery writer

Removing outliers for A/B search tests
engineering

Removing outliers for A/B search tests

How do you measure the success of a new feature? How do you test the impact? There are different ways ...

Christopher Hawke

Senior Software Engineer

Easily integrate Algolia into native apps with FlutterFlow
engineering

Easily integrate Algolia into native apps with FlutterFlow

Algolia's advanced search capabilities pair seamlessly with iOS or Android Apps when using FlutterFlow. App development and search design ...

Chuck Meyer

Sr. Developer Relations Engineer

Algolia's search propels 1,000s of retailers to Black Friday success
e-commerce

Algolia's search propels 1,000s of retailers to Black Friday success

In the midst of the Black Friday shopping frenzy, Algolia soared to new heights, setting new records and delivering an ...

Bernadette Nixon

Chief Executive Officer and Board Member at Algolia

Generative AI’s impact on the ecommerce industry
ai

Generative AI’s impact on the ecommerce industry

When was your last online shopping trip, and how did it go? For consumers, it’s becoming arguably tougher to ...

Vincent Caruana

Senior Digital Marketing Manager, SEO

What’s the average ecommerce conversion rate and how does yours compare?
e-commerce

What’s the average ecommerce conversion rate and how does yours compare?

Have you put your blood, sweat, and tears into perfecting your online store, only to see your conversion rates stuck ...

Vincent Caruana

Senior Digital Marketing Manager, SEO

What are AI chatbots, how do they work, and how have they impacted ecommerce?
ai

What are AI chatbots, how do they work, and how have they impacted ecommerce?

“Hello, how can I help you today?”  This has to be the most tired, but nevertheless tried-and-true ...

Catherine Dee

Search and Discovery writer

Algolia named a leader in IDC MarketScape
algolia

Algolia named a leader in IDC MarketScape

We are proud to announce that Algolia was named a leader in the IDC Marketscape in the Worldwide General-Purpose ...

John Stewart

VP Corporate Marketing

Mastering the channel shift: How leading distributors provide excellent online buying experiences
e-commerce

Mastering the channel shift: How leading distributors provide excellent online buying experiences

Twice a year, B2B Online brings together America’s leading manufacturers and distributors to uncover learnings and industry trends. This ...

Jack Moberger

Director, Sales Enablement & B2B Practice Leader

Large language models (LLMs) vs generative AI: what’s the difference?
ai

Large language models (LLMs) vs generative AI: what’s the difference?

Generative AI and large language models (LLMs). These two cutting-edge AI technologies sound like totally different, incomparable things. One ...

Catherine Dee

Search and Discovery writer

What is generative AI and how does it work?
ai

What is generative AI and how does it work?

ChatGPT, Bing, Bard, YouChat, DALL-E, Jasper…chances are good you’re leveraging some version of generative artificial intelligence on ...

Catherine Dee

Search and Discovery writer

Feature Spotlight: Query Suggestions
product

Feature Spotlight: Query Suggestions

Your users are spoiled. They’re used to Google’s refined and convenient search interface, so they have high expectations ...

Jaden Baptista

Technical Writer

What does it take to build and train a large language model? An introduction
ai

What does it take to build and train a large language model? An introduction

Imagine if, as your final exam for a computer science class, you had to create a real-world large language ...

Vincent Caruana

Sr. SEO Web Digital Marketing Manager

The pros and cons of AI language models
ai

The pros and cons of AI language models

What do you think of the OpenAI ChatGPT app and AI language models? There’s lots going on: GPT-3 ...

Catherine Dee

Search and Discovery writer

How AI is transforming merchandising from reactive to proactive
e-commerce

How AI is transforming merchandising from reactive to proactive

In the fast-paced and dynamic realm of digital merchandising, being reactive to customer trends has been the norm. In ...

Lorna Rivera

Staff User Researcher

Top examples of some of the best large language models out there
ai

Top examples of some of the best large language models out there

You’re at a dinner party when the conversation takes a computer-science-y turn. Have you tried ChatGPT? What ...

Vincent Caruana

Sr. SEO Web Digital Marketing Manager

What are large language models?
ai

What are large language models?

It’s the era of Big Data, and super-sized language models are the latest stars. When it comes to ...

Catherine Dee

Search and Discovery writer

Looking for something?

facebookfacebooklinkedinlinkedintwittertwittermailmail

Headless, composable architecture creates a critical flexibility when building engaging and adaptable product search and discovery interfaces that ensure conversions and increased transactions and ordering. In this article, we discuss how these 3 ingredients, or steps – headless/composable, search/discovery, conversion/engagement – function for a modern, competitive B2B business.

Step 1: Headless/Composable architecture to replace legacy monolithic platforms

Gartner predicts that “By 2023, organizations that have adopted a composable approach will outpace the competition by 80% in the speed of new feature implementation.”

Headless architecture allows freedom and flexibility by removing the link between front-end and back-end. Site content and UI elements can be instantly changed with no effect on the back-end infrastructure. The modern API-first approach offers internal teams (product, marketing, and merchandising) to iterate online omnichannel experiences and test new strategies with high agility and scalability.

B2B Industry leaders, such as Dell Technologies adopt headless, API-first architecture for their ecommerce platforms. The benefits of the headless/composable approach compared to legacy monolithic solutions are highly impactful for any organization:

  • Fast innovation: deploy new features rapidly, have greater control over each feature
  • Lower maintenance costs: have the flexibility to choose the elements and functionality, get automatic software updates instantly
  • Adapt and change easily to any changes in business needs

Composable architecture enables B2B companies to implement an omnichannel sales model, which has proven to be more effective than traditional approaches. Recent research published by McKinsey identified omnichannel as a “critically important fixture for B2B sales globally”, with 83 percent of B2B leaders declaring it as a more successful way to prospect and secure new business than traditional, “face-to-face only” sales approaches.

Moreover, the omnichannel model pattern holds true across multiple geographies, showing enthusiastic adoption trends by B2B companies globally.

Step 2: Product search and discovery

According to Forrester, 92% of B2B purchases start with search. Additionally, Baymard Institute’s recent research found that “Product Type” searches (e.g., “boy’s hoodie”, “sandals”) are almost always the first interaction of users with a site. Product type queries help shape users’ early impressions of what’s available. It is critical to get search relevance configured right to provide relevant results even when user queries don’t match a site’s precise category descriptions. When search results give users the impression of limited or undesired inventory, the risk of abandonment increases significantly.

  • Unify product catalog and ecommerce functionality into a single UX, optimized for multiple platforms
    • Product catalog and shopping platform must be unified
    • Supporting content, such as spec sheets, documents, and papers required to be presented due to various regulations during the sale process and similar documents, should be accessible via a single search bar and linked to a specific product or product category
    • Architecture needs to couple the search engine with the pricing engine. 

Note: For the cases where pricing is dynamic and product prices change frequently, a pricing engine solution should offer real-time pricing data for any pricing complexity level.

  • Product catalog structure: plan which searchable attributes to include (size, product type/category, brand, color, popularity)
  • Relevance settings: ensure fast and efficient product discovery and include and configure B2B specific functionality (e.g. search by SKU)
  • Merchandising: automate products merchandising for campaigns and promotions with tools such as: 
    • Relevance rules (e.g., promoting specific products to the top of the search results list)
    • AI dynamic re-ranking
    • AI synonyms suggestions
    • Personalization
    • Product recommendations

Step 3: Conversions, transactions, and ordering

What are some of the elements to increase conversions and user engagement?

  • Personalized pricing: ensure that each of your business customers is seeing their own custom pre-negotiated prices, discounts, and shipping information, updated in real-time
  • Checkout process simplification: ensure an efficient checkout process, while including all the relevant order information, such as stock/inventory data, tracking, and shipping.
  • Fast and easy re-ordering: B2B shoppers are recurring buyers most of the time; therefore, the re-ordering process should be streamlined and simplified (e.g., personalized search by alias, personalization of search results pages and browse pages, a quick-order button which lets B2B shopper to simply paste the SKUs of the products they want to purchase)

A decision process of choosing the right search and discovery engine for digital transformation of a B2B commerce company:

  • Timelines and urgency
    • B2B shoppers are already well accustomed to the B2C online experience. Their expectations of the B2B world are to match the trends and best practices of B2C ecommerce. Users don’t want to wait any longer today, which poses a risk of churning for B2B organizations lagging behind on online B2B shopping experiences. Therefore, the urgency and priority for digital transformation needs to be high.
  • Infrastructure
    • Performance. There is a clear advantage for a 3rd party engine specifically designed and built from the ground up for speed in critical functions such as search and indexing. You should expect the search engine to deliver lightning fast results and be easily replicable from one platform to another.
    • Reliability. A solution that doesn’t require security or maintenance patches, presents a better alternative to a product with high security maintenance demands.
    • Scale. The need to provision for scale requires vigorous effort and often doesn’t get implemented well due to time constraints, lack of engineering resources, and budgeting limitations. An optimal solution needs to be able to handle large data volumes at any scale.
  • API first vs monolith solutions: the composable/headless approach is an essential tool for future-proofing the company to new trends and challenges. 
    • Easy to build and iterate. The search engine solution should be fully documented (API Clients, front-end libraries). There should be no need to start from scratch when opening a new channel or deploying to a new country or region.
    • Easy to connect / ready for a headless experience. To successfully implement an omnichannel sales model, the search engine needs to connect to all customer touch points. Omnichannel is key for the B2B industry and an optimal way to do business, for instance, ​​apps for salespeople, online catalog, exclusive apps for refurbishment offered only to a specific set of customers, customer support tools, and more.
  • Relevance management
    • White box approach. The search engine should provide transparency over the algorithms it uses to to give control to business teams over ranking and relevance strategies 
    • Dashboard. To function efficiently and react quickly to business trends and challenges, business teams should be able to manage the relevance from a user-friendly dashboard without the need to rely on IT on a daily basis.

Performance, reliability, scalability, and flexibility are the four essential benefits a search and discovery engine should provide to the B2B commerce organization. Open source solutions such as Elastic and Solr are highly resource intensive, requiring a significant amount of engineering resources to maintain and update. While open source solutions appear to be “free”, their implementation and maintenance are costly and time consuming. These difficulties pile up on top of additional challenges, such as lack of transparency regarding the search results ranking algorithms. On the other side of the spectrum are the easy to implement solutions, which are limited in flexibility and scalability, due to their reliance on open source solutions and a cookie-cutter architecture and design. Those solutions suffer from opaque ranking algorithms limitations and are known for their unpredictability when faced with the need to implement modifications or customizations to the relevance ranking of the search results. These will present a significant disadvantage for any B2B commerce company, which are likely to be in need of multiple product modifications. Algolia offers customers a wide range of customizations, to ensure that the product meets each B2B business’ unique requirements and offers the scalability and easy replication from one platform to multiple others.

 

About the author
Tanya Herman

Product Manager

Recommended Articles

Powered byAlgolia Algolia Recommend

B2B commerce digital transformation: Personalization
e-commerce

Tanya Herman

Product Manager

What is B2B ecommerce? Everything you need to know
e-commerce

Vincent Caruana

Sr. SEO Web Digital Marketing Manager

What do the best B2B ecommerce platforms have in common?
e-commerce

Catherine Dee

Search and Discovery writer