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What is retail analytics and how can it inform your data-driven ecommerce merchandising strategy?
e-commerce

What is retail analytics and how can it inform your data-driven ecommerce merchandising strategy?

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8 ways to use merchandising data to boost your online store ROI
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Algolia DocSearch + Astro Starlight
engineering

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What role does AI play in recommendation systems and engines?
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What role does AI play in recommendation systems and engines?

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How AI can help improve your user experience
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How AI can help improve your user experience

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Keeping your Algolia search index up to date
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Merchandising in the AI era
e-commerce

Merchandising in the AI era

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Debunking the most common AI myths
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How AI can benefit the retail industry
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How AI can benefit the retail industry

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How ecommerce AI is reshaping business
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Senior Digital Marketing Manager, SEO

AI-driven smart merchandising: what it is and why your ecommerce store needs it
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AI-driven smart merchandising: what it is and why your ecommerce store needs it

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Unveiling the future: Algolia’s AI revolution at NRF Retail Big Show
algolia

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VP Corporate Marketing

How to master personalization with AI
ai

How to master personalization with AI

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AI Product Manager | On a mission to help people succeed through the use of AI

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Best practices of conversion-focused ecommerce website design
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The way organizations buy, build, and use software is changing.

First, we had on-premise technology. Organizations bought the software and deployed their own infrastructure. Then came cloud technology and Software-as-a-Service (SaaS). Cloud represented a huge leap forward. The days of decrepit server stacks were over. Vendors could deliver a consistently faultless service to their customers. 

But the cloud ecosystem isn’t perfect. The vast majority of tools are siloed. They exist within their own ecosystem, locking in content and organizational knowledge. It creates a mosaic of disparate knowledge management tools, rather than one cohesive system. Organizations can live with technology stacks like these, but it creates inefficiencies and enormous maintenance burdens.

For example, say you want to surface financial reports for the last quarter. You’ll probably have to search through numerous different systems, such as cloud storage, financial reporting, and a CRM. That’s an inefficient way to search for content. 

But there’s an even more serious problem: discovery.

Unless you work at a very small company, you likely won’t know about every system, tool, and service. If you don’t know that your finance team uses a standalone accounting platform, then you aren’t going to search for content in it. In this case, fragmented back-end systems don’t just slow you down, they prevent you from discovering content.

Thankfully, change is coming.

In early 2020, a quartet of Gartner researchers published a paper on the future of applications. They pitched a new idea: composable enterprise.

“A composable enterprise is an organization that delivers business outcomes and adapts to the pace of business change,” they wrote. “It does this through the assembly and combination of packaged business capabilities (PBCs). PBCs are application building blocks that have been purchased or developed.”

In other words, instead of buying functionally narrow tools, organizations will acquire “building blocks” and combine them to construct exactly what they need.

Consider hospitality during the early stages of the COVID-19 pandemic. With most bars and restaurants banned from serving customers indoors, they had to pivot to curbside collection and delivery. How many restaurant website platforms had that functionality? Very few — if any.

With the composable enterprise, companies wouldn’t be constrained by the default functionality of their platform. They could slot together flexible building blocks and launch new functionality incredibly fast.

This new way of buying, building, and using software could transform how organizations use technology. Nowhere is that more true than internal search and discovery.

One search. Multiple back-end systems. 

Right now, every knowledge management system you have includes its own, built-in search functionality — some good, some terrible, some in-between. The composable enterprise means we can discard those variable components and invest in one, dedicated search engine.

A separate component dedicated to search and discovery centralizes data. What does that look like in practice? Think about standard operating practices (SOPs). Different functional teams tend to have different internal wiki preferences. Designers love Notion, developers prefer Confluence, marketers use Google Drive, and so on. With a dedicated search engine like Algolia, those back-office systems can push a subset of their data to the centralized touchpoint. That data is searchable and diverse, meaning it’s structured and schemaless.

If a marketer wants to know more about their company’s software development life cycle (SDLC), instead of searching through myriad internal wikis, they can go to this system-wide search interface, and search for SDLC. The results, drawn from all of the company’s back-end systems, will display either the precise information the marketer is looking for (a summary, report, PDF, etc.) or a link to the piece of content on the back-end system.

Think of it as an internal Google-esque experience. It surfaces data from across your entire company, putting a wealth of historical knowledge at your disposal. You can hopefully see how this addresses the two issues we described earlier: search inefficiencies and discovery roadblocks. It searches everything — even the data sources you didn’t know existed. But it’s also more than just a blanket search.

As part of its centralization, the front-end — what the end user sees — is often federated, offering multiple views, filters, and slices of diverse content. Because this searchable layer is fully API-driven and composable, you can replace, refactor, improve, and extend it. Unlike Google, you fully own the search algorithm. It’s not locked away in a black box. Instead, you can access, edit, and manipulate its inner workings.

Unlocking organizational knowledge

We’re still early in the evolution of search and discovery. Not too long ago, search was a functionality checkbox: does your website have search or doesn’t it? But now, companies are coming around to the power of search and the breadth of its applications. We see the ‘ah-ha’ moment time and time again.

One of our clients, a fashion retailer, kept its entire product catalog index in a composable search tool and was delivering an amazing search experience on their ecommerce website. But then they asked, “How else can this product information be used?” They realized it would be incredibly useful for sales representatives to have access to company-wide product data, so they created an app that allowed them to search the catalog.

Say a customer visits our client’s store to buy a new handbag. With access to all of its internal data, the sales representative can now advise on what fabrics, sizes, and styles are available — not just in that specific store, but neighboring locations, too.

Or suppose a customer’s bag strap snaps when they’re en route to the airport. A support agent can look up inventory for local stores and have a replacement waiting for them when they arrive. Suddenly, they’ve turned support, which is normally deemed a cost center, into a revenue-generating channel.

The most exciting thing about company-wide searchable data is opportunity.

We built Algolia to be headless — both for the front and back ends — which makes it flexible and malleable. Organizations can deploy the composable building block however they wish. That’s precisely what our clothing-retailer client did. No one told them to create an app for sales representatives. They adopted the technology, experimented, and created this functionality themselves. As the technology spreads and more companies experience their ‘ah-ha’ moments, we can’t wait to see what they create.

About the author
Matthieu Blandineau

Sr. Product Marketing Manager

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