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Relative Insight is uncovering the โ€œwhyโ€ behind customer feedback

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Great businesses are great listeners. Paying attention and responding to customers, target audiences, and employees is essential to making a positiveโ€”and lastingโ€”impression on those that engage with your organization. Surveys, online conversations, and customer service interactions all contain invaluable data that can help businesses create better experiences. However, turning unstructured qualitative data into actionable insights isnโ€™t easy.

Together with Amazon Web Services (AWS), the team at Relative Insight is changing that. By leveraging high performance generative artificial intelligence (AI) models in Amazon Bedrock, the company is transforming vast amounts of customer feedback into insightful narrative reports. With Relative Insight, businesses can deliver more valuable experiences and quickly become more responsive to the needs of the people that matter mostโ€”customers.

Transforming unstructured text data into next steps

Founded in 2014 by CEO Ben Hookway, Relative Insight is a UK-based technology and analytics company that helps businesses uncover the โ€œwhyโ€ behind changing key performance indicators (KPIs). โ€œOur mission is to elevate text analytics to improve businesses,โ€ says Hookway. โ€œThat means two things: to improve the quality of text analytics, and to make sure itโ€™s adopted as widely as possible adopted within companies.โ€

โ€œOur key differentiator is our methodology,โ€ says Hookway. โ€œWe compare language sets and then express the differences in the language as metrics. So, for example, your Net Promoter Score (NPS) surveys in May compared to your NPS surveys in April. The difference between the surveys is what youโ€™re really interested in, and thatโ€™s what we produce.โ€

The companyโ€™s most recent offering, Accelerator AI, builds on top of its existing dashboard solution to increase the speed at which customers can uncover and act on insights hidden in unstructured text data. โ€œAccelerator AI takes the metrics that we produce, combines them with raw text data, and automatically produces a narrative report,โ€ says Hookway. โ€œThose reports can then be distributed to stakeholders in the company.โ€

Experiences built on direct customer feedback

โ€œRelative Insight has a number of customers across financial services, large pro sports teams, restaurants, and in the travel industry,โ€ says Oliver Reihill, Head of Product. These businesses use Relative Insight to provide a more enjoyable experience for fans and customers. โ€œMost pro sports teams do fan experience surveys at the end of every game. That data is fed into Relative Insight so that we can understand why the fan experience score is going up, going down, or staying the same,โ€ says Hookway.

Imagine thereโ€™s a lot of discussion around the stadiumโ€™s public address (PA) system being too loud after a particular sports gameโ€”Relative Insight can be used to understand which section of the stadium is experiencing those issues, whether the individuals sat there are season ticket holders or not, how are old they are, and more. Accelerator AI uses that data to create detailed reports so the decision-makers can act quickly to improve fan experiences.

By comparing different metadata points, Relative Insight can also reveal what matters most to different customer segments. โ€œIf you do a comparison between season ticket holders and casual visitors, you will see a difference in what they care about,โ€ says Hookway. โ€œCasual visitors might complain more about transportation, getting to the car park, finding a parking space and so on. Whereas season ticket holders might be more concerned about the facilities, toilets, whether the line is too long, things like that.โ€

โ€œAs far as we understand, weโ€™re the only text analytics platform that is doing these rapid but very detailed and actionable reports, and having that intelligence sent straight out to the people who can actually affect change,โ€ says Hookway. โ€œThis is the key; thereโ€™s no point in having the analytics if you canโ€™t affect the change.โ€

From prototype to product in 8 weeks with AWS Activate

Developing any AI product requires access to high-performance models, trusted expertise, and secure, scalable infrastructureโ€”Accelerator AI was no different. Relative Insight worked closely with AWS to bring its vision for the product to life. โ€œAWS has been instrumental for Relative Insight,โ€ says Hookway. โ€œThey have provided us with technical support while building on the AWS Cloud but also resources around how to innovate very quickly with generative AI, using Amazon Bedrock, and helping us with our go-to-market as well.โ€

The Relative Insight team took part in AWS Activate, a startup-launching program designed to help disruptors rapidly build, launch, and scale on AWS. Startups enrolled in the program can access AWS credits to help them get started with AWS services at no cost, and access proven expertise from AWS Support engineers. Relative Insight used AWS credits to fund experimentation with Amazon Bedrock.

โ€œThe AWS Activate program was really fantastic for us,โ€ says Hookway. โ€œHaving had access to Amazon Bedrock, we turned a prototype into a product inside eight weeks.โ€ Reihill adds: โ€œThat work involves a great deal of experimentation, working with new technology, trying new models, and AWS credits enabled us to do that in a cost effective and scalable way.โ€

Finding the right generative AI model for the job

The Relative Insight team is using Amazon Bedrock to access and experiment with high-performance foundation models (FMs), including large language models (LLMs) from leading providers. Amazon Bedrock is a fully managed service featuring a broad set of capabilities for building generative AI applications with security, privacy, and responsible AI. โ€œAmazon Bedrock gives us the flexibility to pick the right model using AWS infrastructure while still maintaining the security and scalability that we need,โ€ says Hookway.

โ€œWe were able to go to one service to develop against different large language models, as opposed to having to go to individual providers, which would mean more development time, as well as working through the various security and scalability issues,โ€ says Reihill. โ€œNot all large language models are created equal. For different tasks, you need different models. With Amazon Bedrock, we were able to experiment with models and find the right tool for the job. We saved time and effort and achieved cost savings of about ten percent.โ€

Reaching new customers and delivering more value

Beyond technology, Relative Insight has also recently joined the AWS Partner Network (APN). By becoming an AWS Partner, Relative Insight has expanded its reach, delivered greater customer value, and driven profitable growth. โ€œThe AWS Partner Network has been fantastic for us for a couple of reasons,โ€ says Hookway. โ€œOne is that it has facilitated introductions with the customers that we really want to talk to with that credibility of being an AWS Partner. Itโ€™s also introduced us to venture capital companies who are interested in funding Relative Insight as we scale up.โ€

Becoming an AWS Partner has also helped Relative Insight products to be made available on the AWS Marketplace.ย This has helped the company to increase its market exposure, build credibility, and ultimately win new business. โ€œThe AWS marketplace brings a lot of benefits for us,โ€ says Hookway. โ€œWhen youโ€™re selling to enterprise vendors, they want to know that youโ€™re secure, that youโ€™re robust, and youโ€™re scalableโ€”the AWS Marketplace provides all of these things for us.โ€

The Relative Insight team were able to join the AWS Marketplace in a just a few weeks. โ€œAWS is really an enabler,โ€ says Reihill. โ€œGetting us onto the marketplace is key. It allows us to fire up an instance very quickly for a large customer if they want to use our platform in their own instance of AWS. Put simply: it provides more ways for customers to buy Relative Insight products.โ€

Frictionless connection between businesses and their customers

Working with AWS has enabled Relative Insight to innovate, scale, and win new business. โ€œIf we werenโ€™t on AWS, we really would have struggled because as we scaled up and got some really big customers, we would have been straining to support them with the amount of data that goes through Relative Insight,โ€ says Hookway. โ€œBut with AWS, thatโ€™s been a seamless process. We can handle all that data with no problem.โ€

Moving forward, Relative Insight is continuing to collaborate with AWS as it improves its offerings and delivers more value to customers. โ€œWhatโ€™s next for Relative Insight is a real focus on eliminating all friction between the amazing insights we can generate and action in businesses. That means getting reports into the hands of people who need them and bringing the insights that we produce into other systems so that action is automatically taken,โ€ says Hookway.

He continues: โ€œAWS has really helped us with our go-to-market. It exposes us to a bigger breadth of buyers, and itโ€™s given us a much stronger strategic outlook on what we can do and the benefits we can bring to enterprises.โ€ Reihill adds: โ€œThe account management team and all of the solution architects have been invaluable, enabling us to do things that we couldnโ€™t have done without AWS.โ€

โ€œWeโ€™ve got an exciting roadmap heading into 2025. Accelerator AI is coming out now and weโ€™re also looking at areas around voice and other ways of consuming data with our customers. So, itโ€™s a very exciting year for taking our customers from data to knowledge,โ€ says Reihill.

AWS Editorial Team

AWS Editorial Team

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