TECHNOLOGY

Accenture: Traditional loyalty programs waste ‘billions’ in digital age

BY Deena M. Amato-McCoy

Organizations are throwing away billions of dollars annually on customer loyalty programs that just don’t work like they used to.

This was revealed in the Accenture report, “Seeing Beyond the Loyalty Illusion: It’s Time You Invest More Wisely.” The study gauges the experiences and attitudes of 25,426 consumers around the world about their current loyalty relationship with brands and organizations.

Millions of loyalty points are sitting dormant, and the majority of U.S. consumers (78%) are retracting their loyalty at profit-crushing rates. In fact, 54% of U.S. consumers have switched provider in the past year, and almost one fifth (18%) confirmed their expectations around brand loyalty have completely changed, or have a negative or non-existent reaction when brands try to earn their loyalty (16%), the study said.

“Every consumer has a natural instinct around what makes them ‘stick’ to a brand,” said Robert Wollan, senior managing director, global lead of Advanced Customer Strategy at Accenture Strategy. “The traditional ‘low price’ and ‘reliable service’ mechanics are no longer as effective at driving loyalty. New ‘languages of loyalty’ have emerged.”

Key findings regarding these new ‘languages of loyalty’ include:

• Fifty-nine percent of U.S. consumers feel loyal to brands that present them with small tokens of affection, such as personalized discounts, gift cards and special offers to reward their loyalty.

• Forty-one percent of U.S. consumers are loyal to brands that enable them to personalize products, or interact with them through their preferred channels of communication (51%). Meanwhile, 81% feel loyal to brands that respect their time and leave them alone, and those that safe-guard and protect their personal information (85%).

• U.S. consumers are loyal to brands that actively engage them to help design or co-create products or services (44%), or that present them with new experiences, products or services (41%). Furthermore, 33% are loyal to brands that engage them in ‘multi-sensory’ experiences, using new technologies such as virtual reality or augmented reality.

• Consumers are loyal to brands that partner with celebrities (23%), and another 23% feel loyal to organizations that partner with social influencers, such as bloggers and vloggers. Shoppers are also trust brands that their family and friends do business with (42%), or that actively support shared causes, such as charities or public campaigns (37%).

• Consumers feel loyal to brands that connect them with other providers, giving them the ability to exchange loyalty points or rewards (23%), or consistently offering the latest products and services (51%).

“Organizations need to understand the loyalty languages of their most profitable customers and implement the optimal mix to ensure they’re delivering the experiences that drive advocacy, retention and growth,” said Kevin Quiring, managing director, Advanced Customer Strategy, Accenture Strategy. “An appetite for extraordinary, multi-sensory experiences, hyper-personalization and co-creation, are changing consumer dynamics around loyalty and forcing brands and organizations to shift their approaches and programs.”

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TECHNOLOGY

Is Facial Recognition in Retail Market Research the Next Big Thing?

BY CSA STAFF

Remember the memory-erasing Neuralyzer in "Men in Black"? Or more recently, "Ex Machina," the Oscar-winning story of a humanoid robot that uses emotional persuasion to outsmart humans and escape from the secluded home of its creator?

While movies have been envisioning crazy, new technology for decades, some of those inventions are starting to become reality. From virtual reality and wearable devices to facial and emotional recognition technologies, these products and systems are changing the way we communicate, interact and conduct market research (MR) in several industries, most notably, retail.

One of the hottest areas of technology development in retail research is facial and emotion recognition. Understanding emotions is powerful in areas of research such as ad testing, but difficult to achieve. Facial expressions are linked to emotions, and research organizations have used human observation of recorded videos in retail settings to try to assess emotional response for years. Human assessment has many limitations, and facial expression recognition technology offers an opportunity to overcome some of these limitations, delivering a much greater level of insight about personal sentiment and reactions.

Organizations managing research programs and retail customer experience activities can use emotion detection technology to analyze people’s emotional reactions at the point of experience. This knowledge not only gives researchers a greater understanding of behavior patterns, but also helps predict likely future purchasing actions of that consumer.

The result? Remarkable insight into what impacts customer emotions, as well as valuable information that can drive better business decisions, resulting in improved product and service offerings and experiences.

Do we need this? How will we use it?

Competition only continues to grow with retail, making experiences more important than ever. Thus, market researchers are under increasing pressure to deliver business value to their customers. Adding to that pressure is ongoing declining survey response rates and challenges with collecting data from specific demographic groups. Emotion detection provides real opportunities to drive customer spending and enhance loyalty.

The primary use case for those researchers implementing emotional detection is ad testing. Within a survey an advertisement can be shown, during which time, the respondent’s webcam will record their reaction.

Traditionally, respondents will answer questions about the advertisement they’ve been shown, rating it on various scales. While broadly effective in most cases, this is dependent on the respondent’s ability to recall what they’ve just been shown, their interpretation of their own emotions, and their ability to put those emotions into words. Researchers can also observe and record emotions while the video content is being shown, but this needs specific skills and is difficult to perform consistently.

Does it work?

The ability to use video to recognize, understand and report back on the tiniest facial movements doesn’t sound far away from the "Ex Machina" humanoid. Research shows there is a broad array of expressions and micro-expressions that relate to specific emotional responses, and so using technology to capture those facial movements and analyze them against the benchmark data is hugely powerful. Some tests report an accuracy rate of around 95%, which by any measure is impressive.

The technology is already in use by a number of retailers, who have been able to refine their advertising campaigns according to respondents’ reactions to test adverts.

What’s the downside?

If you’re looking at bringing emotion detection into your arsenal, consider the global nature of your programs. People from different nationalities and cultures have different levels of emotional response, and different facial structures, so your benchmark data needs to take this into account.

A second issue to consider is how to deliver your content. While many people are now used to engaging with video content through a variety of media, facial recognition technology requires a two-way view. This means that not only must your respondent be able to clearly and effectively view your video content, they must be in a position where their camera is capturing their expressions clearly. Different lighting levels and different angles of viewing all need to be taken into account.

Finally, you will need to specifically ask respondents for permission to access their webcam and record their faces while they’re watching your content. For many, this won’t be an issue, but if you’re specifically targeting, for example, an older demographic who may think you’ve shifted from curious to creepy, then you may be on safer ground to show video content and ask questions instead of observing their expressions.

Future

Emotion detection software simply adds to the toolkit available to retailers who are looking to improve their customer experiences and create more effective advertising campaigns. It may further reduce the need for focus groups, but beyond that, it’s an addition, not a replacement. Such videos will, in most cases, be embedded into a survey, and additional information will be required to understand more about the shoppers themselves.

No doubt new applications of the software will emerge in both MR and customer experience disciplines – some of which will fly and some of which won’t. As with most advances of the last decade, emotion detection will find its place and help forward-thinking retailers add additional value to the services they provide to their customers. In turn, this will ideally help progress the retail space, helping retailers take their ability to provide customer service and implement customer feedback to the next level.


Terry Lawlor is executive VP of product management at Confirmit, where he is responsible for all aspects of product management, including strategy development, product definition, and product representation in client and marketing activities.

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TECHNOLOGY

Specialty retailer boosts online revenue with enhanced marketing tool

BY Deena M. Amato-McCoy

Driving conversion in a digital landscape requires a new level of engagement.

Pacific Sunwear of California has found a way to reconnect with its digital shoppers, as well as improve its click performance, drive conversion, and thus, sales. Using Rakuten Marketing Search, a solution available through Kenshoo’s advertising platform, the retailer is refining its strategic marketing approach, focusing on consumer engagement (click performance) and automating its ad spend management processes.

PacSun now automatically breaks merchandise into new product groups based on click performance. Meanwhile, automating advertising bids en-sures the company meets its investment goals.

The solution is already helping PacSun stay ahead of the strategic curve in an increasingly competitive digital retail landscape. Since adding the platform, PacSun has dramatically improved its online performance, and achieved a 78% increase in its return on investment (ROI).

The chain also has seen a 16% decrease in cost-per-click (CPC), and 57% increase in conversion by focusing click coverage on top-converting products and bidding down on high-volume, low converting products.

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