Artificial Intelligence

3 Reasons Broken Brick-and-Mortar CX Leads To Failed Brand Experiences

14min
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How we interact with customers in our physical spaces is broken. As customer expectations evolve, physical spaces are no longer keeping up with customer demands. Yet as leaders strive to build a more complete picture of customer behaviors, they continue to rely on decades-old survey-based measurement systems that form the backbone of physical CX efforts.

It's time for our physical spaces to approach how we understand and impact the customer experience in a new way.

Did you know?

80% of customers switch brands because of poor customer experience.

1. Brick-and-Mortar CX Fails to Satisfy the Modern Customers’ Appetite

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The digital age has made consuming information instantaneous and effortless. Shopping, travel, experiences, and work have all become easier for consumers to handle digitally and the optimizations digital platforms have over physical enable them to stay ahead. Customers now expect to see the same digital transformation they have experienced online applied to their offline experiences.

Our physical spaces are lagging behind in their digital transformations and as a result, the gap widens between customer expectations and customer experiences. Customers want hyper-personalization for their preferences, convenience to optimize time spent, and a mobile-first utility at the press of a button throughout their customer journey.

Leaders need to discover new ways of satisfying the modern customers' appetite or risk fading into irrelevancy.

2. Slow Response Times and Frustrated Customers

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How we currently understand our physical spaces results in an information black box. We know what goes in and what comes out, but nothing that happens along the customer's journey without expensive, time-inefficient methods.

Real-world CX is lacking real-time visibility into the customer journey. This means slow response times to customer needs, poor qualitative customer experience, and a failure to support customers' real-time decision making. All of this ends up driving customers away as 80% of customers switch brands due to poor customer experience.

3. Siloed Customer Touchpoints and Subpar Customer Experiences

75% of consumers prefer brands that personalize their experience.
75% of consumers prefer brands that personalize their experience.


With 75% of consumers preferring brands that personalize their experience, the data vacuum companies have on their physical spaces creates massive decision-making hurdles. Companies are simply lacking data and are therefore unable to understand customer sentiment across their customer journey.

Market Research

According to a McKinsey study, less than 6% of CX leaders express confidence that their measurement system enables both strategic and tactical decision making

With current methods to measure the success of customer experience projects being expensive, slow to adapt, and inaccurate, companies only have a fragmented understanding of what happens in location. This means even more additional time and resources wasted on ineffective customer experience projects that just lead to lost business.

AI Bridges the CX Gap By Empowering CX Teams in 3 Ways

Consumers have been spoilt for choice with the convenience and personalization of digital platforms. They expect to use solutions that are available now, not in months or years. Deploying the right solution can enable us to understand our physical spaces quicker, cheaper, and more accurately with limited friction.

Integrating the digital world, namely AI into our physical spaces is becoming inevitable to level the playing field and build delightful customer experiences. AI is collecting data from every touchpoint in the customer journey, filtering only relevant decision-making data, and automatically generating insights. The right CX tool will leverage AI to generate powerful insights and enable innovative customer experiences.

1. Gain A Comprehensive Overview of Your Physical Spaces With AI

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It is impossible to be everywhere at once, even with an army of human agents reporting on every action. Understanding customer sentiment is a never-ending tedious process.

AI Intelligence enables CX leaders to do just that: be everywhere. By being software-based, AI can turn existing hardware like security cameras into powerful sensors that collect accurate data on the quality of the customer experience in a highly scalable way. AI-powered teams gain innovative spatial intelligence to discover friction points to unify silos across customer touchpoints and ultimately understand customer sentiment/journey at physical locations as easily as tracking the customer journey in a digital medium.

Case Example: Understanding Lost Interest With Image Recognition

A fashion retailer executive could not determine why many of its locations failed to bring male shoppers into their stores as well as they did females. They tasked their team to identify issues, and instead of performing a complex survey to understand customer sentiment, took the resources and implemented a computer vision system on their existing security cameras to heat map the shopper journey through their store.

An issue was quickly identified in how certain store layouts were planned. Many stores displayed female clothing at the entrance or first floor of the stores. This resulted in many men leaving the store quickly after entrance once they skimmed through exclusively women's clothing. Computer vision not only enabled the retailer to save the time an analyst would have needed to come to the same conclusion but gained a new method of gaining additional insights into changes they make in the future.

2. Autopilot Actionable Insights For Strategic Decisions

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Deploying the right solutions the first time around would be the dream for any CX team. That would mean no more guesswork after wasting hours of your team’s time struggling to analyze and understand raw data.

By automatically tracking customer patterns to better understand their behavior, AI Intelligence enables customer-facing roles to provide proper attention to customers by prompting alerts and guided actions. In the strategic sense, CX teams gain the information required to justify CX investments and changes.

Case Example: Justifying Investments & Autopiloting Real-Time Decision-making

An international airport tasked its passenger satisfaction team to identify and improve its satisfaction ratings during a $1bn renovation. They decided that to better identify what investments to take, they would apply image recognition software to their existing security camera infrastructure to track passenger flows throughout the terminal.

They quickly identified a bottleneck at the primary TSA checkpoint and used the same computer vision technology to implement a real-time TSA wait time estimation. They provided this knowledge to both passengers to reduce stress, and gate agents to have the decision-making knowledge of when to open new lines to reduce wait time. Through this change, the airport reached second overall in customer satisfaction among airports of its size nationwide, a visible ranking increase in customer satisfaction.

3. Innovate the Customer Experience To Generate Brand Loyalty

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When customer expectations don’t meet customer experiences, you lose important business. Build innovative experiences that take the data you’ve already collected to rapidly adapt to customer demands before they know they need it.

AI Intelligence automatically identifies customer patterns, saving teams the time it takes to identify friction points that hamper a seamless and intuitive customer journey. This enables CX teams to design hyper-personalized experiences that guarantee repeat visits and brand loyalty to become an industry leader in CX.

Case Example: Leading CX By Optimizing Layouts

A major corporate real estate management firm needed solutions to incentivize the employees of its clients to return to the office. With the shift to work at home culture, they needed to provide more value and an experience in an office that doesn't just compete with work at home but complements it. To do this, they needed to understand their space better and rapidly adapt areas to how people use them.

After implementing computer vision and room occupancy tracking, they could automatically generate insights and rapidly collect data that allowed them to test new layouts and initiatives. These led to them implementing daily adjustments to ensure safety regulations, optimize usage, and create new world-class spaces that teams felt more comfortable in.