The Key to Enhancing Customer Loyalty in a Competitive Retail Market

Ritu Dubey
Digitate
Learn more about 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
Learn more about 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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AI is becoming the operating system of the enterprise. It acts as an invisible coordination layer that understands intent, connects systems, and executes work across complex SaaS environments. Previously, employees had to click through multiple systems — CRM, ERP, support tools, collaboration platforms — to complete a single task. Now, instead of navigating each application manually, they can simply state what they need to accomplish ...

The $600 Billion Wake Up Call

In 2026, the cost of downtime or an outage is no longer just a technical inconvenience; it's a $600 billion wake up call for global businesses. As our digital ecosystems become  more interconnected, each touchpoint introduces new risks and multiplies the consequences when things go wrong. And the data is clear: aggregate downtime costs  for Global 2,000 companies have surged 50% since 2024, reaching a staggering $600 billion ...

Breaking Down Agentic AI Fragmentation and Complexity with Governance

Deloitte found that 74% of enterprises expect to deploy agentic AI solutions in the next 24 months. However, the rush to deployment is outpacing foundational work, though. Only 21% of enterprises have fully formed agent governance models in place. The result? AI agents deployed without guidance or governance begin to function as fragmented islands of complexity ...

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Cloud spending is no longer viewed as a passthrough IT expense, but as a strategic financial lever that directly impacts innovation capacity, profitability and enterprise resilience, according to the CFO Cloud Cost Optimization Report from Azul ...

Building AI Agents That Build Trust

As AI moves from generating responses to performing actions, the need for trust increases exponentially. And as organizations enlist AI agents for increasingly sophisticated business processes, trust is going to be the single most important theme for spurring adoption. What can organizations do to build trustworthy AI agents? ...

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I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

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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 ...

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