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The Key to Enhancing Customer Loyalty in a Competitive Retail Market

Ritu Dubey
Digitate

Customer loyalty is changing as retailers get increasingly competitive. More than 75% of consumers say they would end business with a company after a single bad customer experience. This means that just one price discrepancy, inventory mishap or checkout issue in a physical or digital store, could have customers running out to the next store that can provide them with better service. Retailers must be able to predict business outages in advance, and act proactively before an incident occurs, impacting customer experience.

Retailers must be able to predict business outages in advance, and act proactively before an incident occurs, impacting customer experience

Intelligent Automation tools, such as artificial intelligence for Business and IT operations (AIOps), are a key way retailers can create horizontal and vertical visibility of their retail business processes, and transactions, ensuring daily retail readiness and elimination of system failures.

A common business process lead-IT visibility and control delivers the predictability and assurance required by business. By leveraging these technologies, retail IT teams can spend more time focusing on innovations in the customer journey, that can bring in more customers and less time resolving incidents.

The Road to Superb CX Faces Hurdles

While the pandemic created a surge in online shopping, many consumers still prefer human connection and we're already seeing a shift back to brick-and-mortar shopping. Retailers must use various strategies to keep their customers coming back, from financial incentives to top-tier customer service and more. But when retailers don't deliver to customers' high standards, their strategies can easily backfire.

For example, let's say a customer finds an online coupon for a product at their favorite store and decides to pick up five units. Upon checking out, the cashier informs them that the coupon isn't working and spends a few minutes trying to find the issue before raising a ticket. Since the customer was waiting too long, they decide to leave the store and purchase from a competitor who offers the same product at a lower cost. Behind the scenes, this discrepancy could have been a minor IT issue on the retailer's end, but the customer will view it as the retailer failing to deliver a promised discount.

Digital systems, like ERP and CRM, power the retail industry and it's critical that they continue running without disruptions. As we saw with our customer example, each second of downtime takes away from the customer experience (CX), leaving customers frustrated and decreasing brand value in the market.

This means IT teams must find and fix issues quickly and effectively. However, considering how today's IT systems generate thousands of tickets per second, doing this manually would be impossible.

AIOps to the Rescue

Retailers need tools that can help them solve issues proactively rather than reactively to avoid losing customers and tarnishing their brand reputation. AI and automated technologies, like AIOps, are retailers' golden ticket to securing more customers and beating their competition.

AIOps technologies leverage the power of machine learning, big data and other analytics tools to strengthen IT operations through business function monitoring and business transaction monitoring by building common visibility of business processes and business transactions enabling end to end control of operations and high business assurance, thereby driving a highly predictable and autonomous enterprise. These tools can find the root cause of an IT issue and immediately notify teams. From there, they can suggest the most effective way to permanently fix the problem and do so autonomously and without human intervention required. They can also learn from historical trends to predict future failures and provide preventative steps for proactively getting ahead of an incident.

If a customer's online coupon isn't working at checkout, an AIOps system might find that the root cause is a price and promotion data reconciliation problem and self-heal it in seconds, without a need for IT involvement. As a result, the customer will leave happy and would be likely to come back.

The Future of Retail is Digital

With so many brands competing for the same thing, consumers expect a positive and frictionless experience, whether that be online or in store. By leveraging AI and automation-based tools, retailers can feel confident that they are providing an excellent customer experience on repeat and without failure. In a digital-first era, retailers with seamlessly operating technologies will be the ones to lead the market.

Ritu Dubey is Global Head of New Business Sales and Market Development at Digitate

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The Key to Enhancing Customer Loyalty in a Competitive Retail Market

Ritu Dubey
Digitate

Customer loyalty is changing as retailers get increasingly competitive. More than 75% of consumers say they would end business with a company after a single bad customer experience. This means that just one price discrepancy, inventory mishap or checkout issue in a physical or digital store, could have customers running out to the next store that can provide them with better service. Retailers must be able to predict business outages in advance, and act proactively before an incident occurs, impacting customer experience.

Retailers must be able to predict business outages in advance, and act proactively before an incident occurs, impacting customer experience

Intelligent Automation tools, such as artificial intelligence for Business and IT operations (AIOps), are a key way retailers can create horizontal and vertical visibility of their retail business processes, and transactions, ensuring daily retail readiness and elimination of system failures.

A common business process lead-IT visibility and control delivers the predictability and assurance required by business. By leveraging these technologies, retail IT teams can spend more time focusing on innovations in the customer journey, that can bring in more customers and less time resolving incidents.

The Road to Superb CX Faces Hurdles

While the pandemic created a surge in online shopping, many consumers still prefer human connection and we're already seeing a shift back to brick-and-mortar shopping. Retailers must use various strategies to keep their customers coming back, from financial incentives to top-tier customer service and more. But when retailers don't deliver to customers' high standards, their strategies can easily backfire.

For example, let's say a customer finds an online coupon for a product at their favorite store and decides to pick up five units. Upon checking out, the cashier informs them that the coupon isn't working and spends a few minutes trying to find the issue before raising a ticket. Since the customer was waiting too long, they decide to leave the store and purchase from a competitor who offers the same product at a lower cost. Behind the scenes, this discrepancy could have been a minor IT issue on the retailer's end, but the customer will view it as the retailer failing to deliver a promised discount.

Digital systems, like ERP and CRM, power the retail industry and it's critical that they continue running without disruptions. As we saw with our customer example, each second of downtime takes away from the customer experience (CX), leaving customers frustrated and decreasing brand value in the market.

This means IT teams must find and fix issues quickly and effectively. However, considering how today's IT systems generate thousands of tickets per second, doing this manually would be impossible.

AIOps to the Rescue

Retailers need tools that can help them solve issues proactively rather than reactively to avoid losing customers and tarnishing their brand reputation. AI and automated technologies, like AIOps, are retailers' golden ticket to securing more customers and beating their competition.

AIOps technologies leverage the power of machine learning, big data and other analytics tools to strengthen IT operations through business function monitoring and business transaction monitoring by building common visibility of business processes and business transactions enabling end to end control of operations and high business assurance, thereby driving a highly predictable and autonomous enterprise. These tools can find the root cause of an IT issue and immediately notify teams. From there, they can suggest the most effective way to permanently fix the problem and do so autonomously and without human intervention required. They can also learn from historical trends to predict future failures and provide preventative steps for proactively getting ahead of an incident.

If a customer's online coupon isn't working at checkout, an AIOps system might find that the root cause is a price and promotion data reconciliation problem and self-heal it in seconds, without a need for IT involvement. As a result, the customer will leave happy and would be likely to come back.

The Future of Retail is Digital

With so many brands competing for the same thing, consumers expect a positive and frictionless experience, whether that be online or in store. By leveraging AI and automation-based tools, retailers can feel confident that they are providing an excellent customer experience on repeat and without failure. In a digital-first era, retailers with seamlessly operating technologies will be the ones to lead the market.

Ritu Dubey is Global Head of New Business Sales and Market Development at Digitate

Hot Topics

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As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...