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GUEST COMMENT The top three ways to fuel ecommerce hypergrowth using augmented analytics

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GUEST COMMENT The top three ways to fuel ecommerce hypergrowth using augmented analytics

Alexander Igelsböck, CEO and Co-Founder, Adverity
Alexander Igelsböck, CEO and Co-Founder, Adverity

Retail will make up 20% of this year’s total digital ad spend, rising 8.4% from 2019 to more than £3 billion. As a result, retailers are moving fast to adapt to changing consumer habits that look set to stay – with 17.2 million UK shoppers predicted to shift permanently online – meaning the pressure is on to harness data insights and capture valuable sales.

 

But in a digital landscape saturated with data, identifying the most valuable intelligence can be like looking for a needle in the proverbial haystack, and every minute spent searching can result in a missed conversion.

 

AI-powered, augmented analytics is an essential tool for producing informed, highly effective digital strategies that boost retailers’ bottom lines. By breaking down data silos between retailers’ marketing, sales, and customer service departments, alongside introducing greater automation to the analytical process, augmented analytics offers an advanced means of securing a competitive edge.

 

Deploying augmented analytics transforms data-driven approaches into insight-driven ones, surpassing traditional business intelligence tools with its predictive capacity and ability to identify the most critical consumer data – as well as show retailers how best to act on it. As data-driven practices continue to evolve, many retailers are now harnessing augmented analytics to re-evaluate how to better serve customer behaviour, and meet expectations, in a landscape where new consumer habits are being shaped, influenced and accelerated by the pandemic and resulting lockdowns. So how can retailers fuel their ecommerce success using insights derived from data?

 

1.Progress from business intelligence to augmented analytics

 

To gain a historical view of performance data, retailers have typically relied on business intelligence to show the outcomes of digital advertising strategies. While spreadsheets and reports provide useful indicators of success, their value is largely retrospective. Business intelligence is limited when it comes to predicting upcoming events and allowing advertising teams to learn how potential trends will impact their profits. In an increasingly dynamic market, it has become vital for retailers to understand how disruptions will influence their business so that they can pivot accordingly – ahead of time.

 

Through its combination of data analytics and AI, augmented analytics operates continuously to monitor consumer habits and enhance retailers’ insights in real time. It can correlate structured and unstructured data to deliver strategic recommendations faster, as well as shed light on obscure patterns and data anomalies. By automating the cleansing, sorting, and unifying of data, augmented analytics expedites the process for generating insights, while also showing retailers how to implement these in their ad campaigns. This leads to a proactive, adaptable approach that ensures retailers aren’t leaving money on the table while they adjust their digital strategies.

 

2. Pull critical insights from the data haystack

 

Data’s key value is its ability to inform successful decision making. Retailers need rapid, actionable insights to enhance their online ad campaigns, but drawing this out of the figurative ‘data haystack’ can be challenging. With access to more data than ever before, retail brands need to define what is relevant, accurate and trustworthy. Recent research shows that only 20% of all raw business and operational data is retained for analytical purposes, due to the vast amount of time it takes to make sense of complex datasets.

 

Consequently, it is easy for retailers to overlook possible threats and valuable opportunities, highlighting the importance of building a single source of truth. This was a key challenge for market leader IKEA, which wanted to make the most of its rich data assets but needed improved accessibility and data processing tools. Through implementing augmented analytics, IKEA was able to effectively increase the performance of its digital advertising with highly detailed, in-depth granular insights. Additionally, automating its data processes meant that time and resources could be better utilised in executing strategic adjustments and driving results, as opposed to lengthy data trawling and interpretation.

 

By turning data into actionable steps, IKEA was able to adopt an insight-driven approach to inform all aspects of its digital strategy. From ad targeting to the customer experience, retail brands can follow the same path to achieve effective optimisation. With a clear view of data assets, IKEA could set benchmarks and targets for performance, then automate notifications to monitor success and make sure it could continuously adapt to meet these goals. Having this information to hand – in the form of intuitive charts and dashboards – streamlined the adaptation process, while also providing drill-down capabilities for more detailed data analysis.

 

3. Accurately detect emerging trends and maximise performance

 

To stay ahead of the curve, retailers must take a proactive, forward-thinking stance to enhancing their online campaigns. With augmented analytics, brands can automatically detect trends as they emerge, for instance changes to the market or unexpected consumer behaviours. Through sophisticated analysis of historical data, this technology can predict the relevance of changes and simulate how they will impact advertising revenues. Retail brands can then plan, execute, and pivot strategies in advance to optimise performance.

 

Alongside this, ongoing segment analysis based on consumers’ location, age, or device type provides insight into the relative success of each. Leveraging this technology, retailers can identify under- and over-performing segments, then refine targeting strategies to reduce drains on budget and make every penny of ad spend count. When these segments are detected, augmented analytics presents advertisers with a visualisation that details potential gains and actionable changes. This process feeds into retailers’ proactive mindset, enabling them to both prepare for disruptions and instantly react to insights.

 

Digital advertising may start with data, but retailers need the means to transform this into rich consumer insights that can achieve gold standard online campaigns. By streamlining data processes and building a comprehensive view of campaign performance, augmented analytics offers retail brands the means to stay ahead of competitors, boost revenues, and become agile in today’s economic climate.



Author:

 

Alexander Igelsböck, CEO and Co-Founder, Adverity

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