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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

The Latest

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...

When most people think about cybersecurity, they picture firewalls, encryption, and access controls — technical tools designed to protect systems and data. But beneath the technology lies a deeper set of principles about trust, decision-making, and resilience ... The best leaders don't eliminate risk. They manage it intelligently. And in many ways, cybersecurity offers a surprisingly useful playbook for doing exactly that ...