Leading search analytics company, Elastic recently held its ElasticON Tour in Sydney, hosting demonstrations, breakout sessions, and networking opportunities with industry experts and Elasticsearch customers. 

Retailbiz sat down with Elastic area vice president of Australia and New Zealand, Gavin Jones to hear about the event and how search powered AI enables businesses to find accurate, insightful and relevant answers in real time, at scale.

“ElasticON is our global flagship event that spans 12 cities worldwide, covering the US, EMEA, APAC and Japan. It’s a major event for us and it was the first ElasticON held in Sydney since before Covid. This year, it was five times the size of the last event and there were over 570 attendees, which is a real testament to Elastic being top of mind, relevant and providing solutions that matter to our customers and partners,” Jones said. 

“It was the first ElasticON event worldwide with all three major hyperscalers sponsoring the event – Amazon Web Services, Google Cloud and Microsoft. We had an incredible line-up of speakers from those sponsors, as well as Canva, Macquarie Bank, National Australia Bank (NAB), Southern Cross Austereo, Sovereign Wealth Fund of Australia and many more. 

“There were lots of insights shared by Elastic, our partners and our customers, but they were mainly centred around two major themes. The first was generative AI, and Elastic has been leveraging machine learning (ML) and AI in driving product innovation for over 10 years, but it has thrust us into the forefront of transforming the industry and leading that narrative around Gen AI.

“Elastic is the trusted bridge between public Large Language Models (LLM) and co-pilots to ensure private and confidential data isn’t put into the public arena. We’re the bridge between that confidential data and the multiple LLMs in the market.” 

“I hosted a panel on Gen AI around harnessing the power of data and Gen AI, looking at the risks and ethical considerations, but also the massive potential. I think the general consensus was that human touch is still important and dispels the fear of job losses for robots.

“The other major theme was security. Elastic was recently recognised by Forrester as being the visionary leader in security analytics, ahead of our traditional and legacy competitors. We combine observability that looks at internal threat vectors, as well as cybersecurity to provide a 360-degree view of security.

“The event looked at the importance of redefining risk posture and threat detection in cybersecurity, viewing it more as a business risk, rather than a technical risk, shifting towards embracing that open security model.”

Gen AI could unlock billions of dollars in economic value 

A recent report released by Microsoft in collaboration with Tech Council of Australia, Australia’s Generative AI Opportunity, shows that Gen AI could contribute as much as $115 billion a year to the local economy by 2030 by improving existing industries and enabling the creation of new products and services.

“In the retail and consumer packaged goods (CPG) industry specifically, Gen AI is a rapidly evolving landscape. Technological advances have been instrumental in shaping many facets from customer engagement to inventory optimisation and predictive maintenance in supply chain,” Jones said. 

“Organisations recognise that if they leverage Gen AI, they can achieve a competitive advantage to meet changing consumer demands and stay ahead in this increasingly digital and data driven marketplace. However, despite the enormous potential of Gen AI, many organisations are struggling with where to start, the risks and the security considerations and complications.

“Gen AI is changing the way retailers bring solutions to market and engage with customers. It can assist and guide the entire purchase journey to create a more engaging and efficient shopping experience. It can aid in summarising context around shopping history, and when it’s coupled with vector search, it can help accelerate the retrieval of similar items based on semantic search.

“Retailers can also efficiently achieve personalisation at scale, while focusing their talent and expertise on driving business results and enhancing core operational and organisational competencies.”

One area Elastic has been investing in is our Elasticsearch Relevance Engine (ESRE); a suite of flexible tools that play an integral role in helping businesses develop search-powered AI applications. 

“It merges ML capabilities with text search, enabling ecommerce developers to enhance search applications using sophisticated algorithms that integrate with LLMs. Importantly, it also helps them address the challenges associated with Gen AI, like privacy, scalability and cost considerations.”

Paradigm shift in personalisation and customer expectations 

With AI and ML innovation happening at such a rapid pace and as the market continues to mature, Jones expects to see further advancements in search which will challenge what personalisation means today and how the search experience becomes even more relevant for the shopper of tomorrow. 

“Retailers need to leverage these capabilities to reach new audiences and meet new expectations around hyperpersonalised shopping experiences including search,” he said. 

“There will be an increase in cybersecurity and infrastructure requirements, particularly in retail as consumers put sensitive and financial data on the web, making them an easy target. We need to protect customer data to prevent theft and fraud, as well as comply with regulations to take advantage of, and adopt, new technologies.” 

A recent report from the Australian Payment Network showed card payment fraud – referred to as Card Not Present (CNP) – costs the Australian ecommerce industry about $495 million each year – and it’s only accelerating. 

“Traditional reactive responses to fraud management aren’t adequate anymore, especially in the face of these evolving threats. It’s necessitating a proactive, customer-centric approach that integrates advanced technologies like AI and ML, actionable insights and analytics, as well as enhanced authentication methods,” Jones said.

How global retailers use Elastic to improve operations

Retailers around the world are using Elastic’s capabilities for personalised search experiences, enhanced customer service, fraud detection, predictive maintenance and modernising bricks and mortar business models. 

“If we look at personalised search experiences, Gen AI facilitates a highly tailored experience by analysing user preferences and ESRE provides robust search capabilities, allowing retailers to build fast and relevant search experiences, combined with Gen AI, that take into account location, demographics and prior purchase history designed to ultimately improve satisfaction and retention,” Jones said.

“There are many comprehensive search and analytics tools that Elastic provides. Combined with real time analytics and ML, it allows retailers to finetune the buyer journey, optimise the product offering and drive sales.”

Companies like Adobe, eBay and Home Depot leverage Elastic’s technology to build robust search and discovery applications, but also to take advantage of the flexibility, scalability and advanced features around personalised search.

“If you look at customer service, the ability to use Gen AI to analyse historical customer data and generate automated responses to things like FAQs and common issues is an important area. ESRE supports that use case by offering semantic search capabilities, which helps customers find information more quickly, streamlines the self-service support process and allows sales agents to focus on more complex queries,” Jones said. 

One of Elastic’s customers, Shopify, is generating valuable content by eliminating the need for ongoing maintenance and leveraging Elastic Site Search capabilities and analytics to better respond to customer queries, analysing search data and support tickets to identify documentation gaps and prioritise content creation. 

“Fraud detection is another major area of focus and Gen AI can assist in identifying fraudulent activities through pattern learning, not through pre-built rules, but by identifying anomalies that people may not have been looking for, things that are outside of normal behaviour.

“You can build rules and use ML and AI, but Gen AI is actually looking for patterns that you may not even know you’re looking for, and it can surface those sooner than a human recognises the threat.”

Another Elastic customer, Walmart, uses the Elastic Stack and they’ve now processed over four billion metadata records in the last five years to tackle fraud and keep customers safe. 

“They’re feeding IP addresses, point of sale information and other traffic data into Elasticsearch. The Walmart risk analysis team can promptly detect instances of fraud, which are often targeted at senior citizens using gift cards, but they’ve been able to detect and shut those fraud cases down.

“If you look at operational efficiencies, Gen AI combined with data from various sources can assist retailers predict when equipment failures will occur and optimise their operations. The system looks at patterns and anomalies to alert retailers where there could be breakages in their supply chain and looks at preventative maintenance to prevent it happening in the first place.

“ESRE enables retailers to automate monitoring and accelerate analysis, while optimising operations through ML to improve productivity, innovation and the customer experience.”

What’s next for Elastic?

Gen AI and security will continue to be two key areas of focus for Elastic in the years ahead.

“In November 2023, we released version 8.11, of the Elasticsearch platform and as part of that, we released the technical preview of Elasticsearch Query Language (ES|QL). This is a foundational platform innovation used across all our solutions, designed to transform and enrich, but also simplify data investigation. It enables data aggregation and analysis across various data sources all from a single query,” Jones said.

“What does this mean for retail customers? It enables both retailers and consumers to find exactly what they’re looking for instantly, as it takes on more complex queries. It delivers the ability to personalise the customer journey using real time company data, providing tailored search recommendations and creating expanded pathways for both consumers and employees.” 

In the APAC and Japan region, Elastic is driving the expansion of its partner ecosystem to add value to retailers. 

“In ANZ alone, we have increased our resources for our partners by fivefold with some specialists in the retail sector. It’s not only about expanding and scaling our business but driving that impact and outcome for our customers.”

In 2024, Elastic is also focused on helping customers migrate to cloud; a shift that’s only accelerated since Covid. 

“It’s a trend we’ve seen for a number of years but for us, we’re focusing on helping customers tap into the financial benefits of migrating to cloud. Equally, the competitive advantages it provides retailers, especially as they look to enhance the shopping experience and achieve higher conversion.”