Before a customer logs in, loads a product page, or checks their order history, a cascade of invisible processes has already run. A database has retrieved its information. An API has connected the relevant systems. An automation has triggered the right response. A messaging system has delivered the update they needed. None of it is visible. All of it is felt.

That invisibility is the measure of a successful backend. When these systems work, customers experience so little friction that they never think about what is happening beneath the surface. When they fail — when a page loads slowly, a transaction stalls, or a notification arrives too late — trust in the platform erodes immediately. Users rarely articulate why an app feels unreliable. They simply stop using it.

For technology leaders focused on customer experience, understanding how backend infrastructure shapes what users actually feel — not just what they see — is becoming a strategic priority.

Databases: Speed Is the Product

A database stores everything that keeps an application running: customer profiles, order histories, product catalogs, login credentials and activity records. Every time a user interacts with a platform, the system is querying that database in real time.

The margin for error is narrow. Research has shown that a one-second delay in page load time reduces conversions by seven percent. At scale, that figure compounds quickly. A database that responds in milliseconds produces a customer experience that feels instant. One that lags results in a customer leaving.

Integrations: One Experience Across Many Systems

Most businesses today operate across a dozen or more software tools simultaneously — customer relationship management platforms, payment processors, marketing automation systems, analytics dashboards. Without integrations, these systems operate in isolation. With them, they share data in real time and present a coherent experience to the user.

The practical effect is visible in small moments. When a customer updates their phone number and sees the change immediately reflected in their support correspondence and email communications, that seamlessness is the product of well-built API integrations working behind the scenes. The same infrastructure enables personalization: research suggests that around 72% of recipients engage only with messages tailored to them, making the ability to link customer data to behavioral signals a direct driver of revenue.

Automations: Removing Friction Before Users Notice It

Automation handles the repetitive processes that keep operations running without human intervention — confirmation emails sent after purchases, support tickets assigned to the right team, profiles updated, and marketing messages scheduled. For users, these automations are invisible. What they experience instead is speed, consistency and the feeling that the system anticipated what they needed.

More sophisticated applications are emerging. AI-powered behavioral analysis can reveal why users abandon items in their shopping carts, identify friction points in checkout flows and suggest layout changes that improve conversion — all derived from patterns in backend data that no human analyst would have the capacity to review at scale.

Messaging Systems: Timing Is Everything

Customer expectations around communication have sharpened considerably. Research indicates that around 40% of users expect a response within an hour, and 79% within 24 hours. When a response arrives while a concern is still relevant — whether from a human agent or a well-designed chatbot — it builds confidence in the platform. When it arrives late, the moment has passed and the damage is done.

Real-time messaging infrastructure makes transparency possible at scale. Delivery updates, appointment reminders and account alerts arrive exactly when they are needed, without manual intervention. For smaller businesses operating with limited customer service resources, this infrastructure allows them to meet expectations that were previously achievable only by larger organizations.

The Backend Is the Brand

A polished interface can attract a user. It is the backend that keeps them. The systems that store, connect, automate and communicate are not technical details — they are the foundation on which every customer relationship is built. Users may never see them. But they feel them with every interaction, and they remember how the experience made them feel long after they have forgotten what the interface looked like.

The post The Invisible Infrastructure Behind Every Great App appeared first on MartechView.

Introduction

Net Promoter Score (NPS) has established itself as a popular metric for evaluating customer loyalty, satisfaction levels, and the likelihood of customer churn. Widely adopted across industries, NPS has faced increasing scrutiny for its limitations in offering a complete view of the customer experience. This article delves into these critiques, exploring how NPS fares across diverse business landscapes in B2B and B2C environments.

Furthermore, it investigates contemporary global trends in customer feedback strategies that advocate for a shift beyond simplistic metrics. By embracing a more nuanced approach, organizations can understand customer sentiment comprehensively, facilitating more informed decision-making and enhancing overall customer satisfaction.

The Limitations of NPS

NPS, encapsulated by a single question—” How likely are you to recommend us?”—offers a narrow and momentary transactional perspective on customer sentiment. Despite its simplicity, more than 75% of organizations are projected to phase out NPS as a Measure of Success for Customer Service and Support by 2025, according to Gartner. This simplicity overlooks the complexity of customer relationships and experiences, failing to capture nuanced feedback crucial for improving overall customer satisfaction.

Companies such as Toyota and Samsung, prominent in Asian markets, have found that while NPS provides a snapshot, it lacks depth in identifying evolving customer expectations and perceptions. It’s essential to move beyond singular transactional satisfaction and focus on consistent, longitudinal insights to truly understand customer behavior and preferences.

The same criticism can be made about every metric for everything. In CX, the same applies to CSAT, CES, and whatever. In accounting, your Net Operating Profit number tells you nothing about causes. In health, your heart rate at 160 tells you nothing, and nor does your blood pressure on its own; without all factors and influencer results of your health, you cannot drive conclusions, for example, knowing whether you were running at the time were you in the Gym, running or Jiu Jitsu training, this already will influence your momentary pressure results.

In the report, Gartner mysteriously states that CSAT provides better diagnostics than NPS, but that is false. It provides another kind of feedback, a different angle of needed feedback. No number or response provides any diagnostics on its own. The main point is that we are talking about NPS, but no individual metric can supply all the needed information; therefore, I called this article “360 Degree Revolution” since all metrics plus data supply your organization with a much better reality check than anything else.

Also Read: Building Lasting Customer Relationships in the Humanized Age of CX

Should you kill NPS? Not now—it is still important as one metric that provides a limited view of the customer transaction. I did not suggest to companies that they should use NPS, too, especially the egocentric number that often gives a dopamine moment for the C-suite when they should not focus on the number since it doesn’t matter in the end.

I am not sympathetic to NPS as it works as a transactional matter, but for one minute of satisfaction, if that is what you are looking for, maybe that is enough. We do not advise this approach for anyone but advocate for using smart metrics that entail the entire experience over a certain amount of time. Choose what matches your organization. I hope this makes sense; if not, I am interested in your thoughts.

B2B vs. B2C Perspectives

In B2C environments, where transactional interactions are straightforward, and brand loyalty is clearer, NPS can be a reliable indicator of customer advocacy and satisfaction. European giants like Unilever and Siemens utilize NPS to gauge consumer sentiment and pinpoint areas for product line improvements. However, NPS often falls short in B2B sectors characterized by complex decision-making processes and long-term partnerships.

Sony and LG in South Korea illustrate the challenges of applying NPS effectively in environments where sustained service excellence and relationship management are paramount. Comprehensive feedback from multiple sources, integrating Voice of the Customer (VOC), metrics, measurements, data analytics, real-time sentiment analysis, and evolving AI developments, is essential for a complete customer understanding.

Like all the companies I know, Siemens and Unilever use several metrics, data analytics, and KPIs to drive conclusions. Any company that understands the basics must have additional questions and metrics beyond a simple rating or question. For instance, a company’s operating profit is useless without additional metrics and supporting information.

Companies Supporting NPS Globally

Global corporations like Alibaba in China and SAP in Germany continue to endorse NPS as a valuable metric for understanding customer sentiment and fostering growth. These companies integrate NPS into broader customer experience strategies, complementing it with additional qualitative insights and metrics to paint a comprehensive picture.

Medallia, based in the US, provides platforms supporting NPS implementation across diverse international markets, emphasizing the need for localized approaches to customer feedback. Thousands of companies around the world echo this practice. Metrics such as NPS, CSAT, CES, ACSI, and double-blind benchmark scores are most valuable when integrated into broader customer experience strategies.

Like many other companies, Siemens and Unilever use several metrics, data analytics, and KPIs to drive conclusions. Any company that understands the basics must have additional questions and metrics beyond a simple rating or question. For instance, a company’s operating profit is useless without additional metrics and supporting information.

Also Read: All You Need To Know: Customer Effort Score (CES)

The Rise of Data Analytics and AI and Real-Time Feedback

Advancements in data analytics and real-time feedback mechanisms are revolutionizing how companies collect and utilize customer insights globally. Japanese e-commerce giant Rakuten and French beauty leader L’Oréal leverage AI-driven analytics to monitor sentiment across digital platforms, enabling proactive responses to customer feedback. This paradigm shift challenges the retrospective nature of NPS surveys, offering immediate insights that inform strategic decision-making and enhance overall customer satisfaction.

AI avoids survey bias by covering 100% of customers and addressing the tendency of survey respondents to be more positive about a company than non-respondents, which can vary by culture. Additionally, AI is continuous, using operational data to generate information expressed through existing metrics and KPIs, facilitating easier communication within the company.

To achieve a genuine 360-degree understanding of customer sentiment, organizations are adopting a range of metrics in addition sometimes to NPS:

• Customer Effort Score (CES): Measures the ease of interaction and issue resolution.

• Customer Satisfaction (CSAT): Evaluates satisfaction with specific interactions or transactions.
• Customer Lifetime Value (CLV): Estimates revenue potential from a customer over their lifetime.
• Revenue Growth: Tracks growth directly attributed to customer experience initiatives.
• Customer Retention Rate (CRR): Measures the ability to retain customers over time.
• Return on Investment (ROI): Calculates profitability from specific CX investments over time, comparing gains against costs.

NPS: Predictive and Reactive

Traditional Net Promoter Score (NPS) feedback often reflects historical data of about one interaction, assessing customer satisfaction at a specific moment. However, its relevance diminishes with delayed insights. Businesses can shift from reactive to proactive strategies by understanding customer concerns in real time.

Effective leadership necessitates leveraging real-time service data and AI to gain a comprehensive view of the customer journey and sentiment upfront. This data-driven approach enables informed decision-making based on precise analysis, moving beyond instinctual transactional responses to dynamic customer sentiments.

In today’s volatile environment, customer sentiment can change rapidly. Only a coordinated sequence of data, measures, and metrics can provide a comprehensive view, ensuring customer satisfaction before and after interaction. Consequently, real-time insights and predictive analytics render reactive NPS less critical, emphasizing anticipating and addressing customer needs before they arise.

Also Read: Why Attention Metrics Matter in 2024

Implementing Effective Customer Feedback Strategies

Companies must define clear metrics, measures, data sources, scorecards, and KPIs aligned with strategic goals to effectively utilize these metrics. This approach ensures a comprehensive evaluation of customer experience efforts, fostering continuous improvement and adaptation to evolving customer expectations. Companies like Tencent in China and Nestlé in Switzerland exemplify the integration of diverse metrics to drive customer-centric strategies and enhance long-term customer relationships. Yes.

Cultivating a customer-centric Culture: Strategies for Sustainable Growth Beyond NPS

To achieve a comprehensive 360-degree customer feedback system for both B2B and B2C environments, several key elements are essential:

1. Multi-Channel Feedback Collection: Utilize surveys, social media listening, feedback forms, and direct interactions to capture diverse perspectives across various touchpoints.
2. Segmentation and Personalization: Tailor feedback mechanisms to different customer segments to enhance relevance and effectiveness.
3. Continuous Feedback Loop: Establish real-time feedback loops for immediate responses to customer issues and ongoing improvements.
4. CRM Integration: Correlate feedback data with customer profiles and transaction history for deeper insights into behavior and preferences.
5. Advanced Analytics and AI: Use these tools to analyze large volumes of feedback data, identifying patterns, trends, and sentiment.
6. Cross-functional collaboration: Ensure feedback insights drive strategic decisions and improvements across all departments.
7. Clear Metrics and KPIs: Align metrics with business objectives to measure the effectiveness of feedback initiatives and track improvements.
8. Cultural and Regional Sensitivity: Ensure feedback methods and interpretations are relevant across diverse customer bases.
9. Customer-Centric Culture: Foster a culture where feedback is valued and acted upon at all levels, promoting continuous improvement and innovation.

Conclusion

While Net Promoter Score (NPS) continues yet to serve as a valuable metric alongside others for gauging customer loyalty and satisfaction, its limitations in capturing the full spectrum of customer experience are increasingly apparent in today’s global markets. The reliance on a single, simplistic question—” How likely are you to recommend us?”—fails to provide the depth of insight necessary to truly understand and address evolving customer expectations. In the end, why do we talk so much about NPS? Because an entire sector has pushed it forward, and its adoption went well for many years.

Also Read: Mastering LTV: Data Analytics and Attribution

The emergence of advanced data analytics and real-time feedback mechanisms presents a transformative opportunity for organizations to transcend the constraints of NPS. By embracing a diverse array of metrics and leveraging cutting-edge technologies such as artificial intelligence (AI) and machine learning (ML), businesses can obtain a more comprehensive and nuanced understanding of customer sentiment and other important facts. This holistic approach facilitates proactive decision-making and enables organizations to anticipate customer needs and deliver personalized experiences that drive loyalty and satisfaction.

Furthermore, integrating qualitative insights alongside quantitative metrics allows a deeper exploration of customer motivations, preferences, and behaviors. While NPS remains a useful tool among many others, evolving it into a broader ecosystem of customer feedback strategies is essential for businesses aiming to thrive in today’s dynamic markets. The market is progressing thanks to AI, and the advice to use multiple metrics is now more relevant than ever.

By embracing diversity in metrics and harnessing the power of advanced technologies, organizations can unlock deeper insights, foster meaningful customer relationships, and position themselves as leaders in customer experience excellence. The reliance on any single question or metric fails to provide the depth of information needed to achieve these goals.

The post Beyond NPS: Why Customer Feedback Needs a 360-Degree Revolution appeared first on MartechView.

Move beyond data dashboards and embrace the heart of CX excellence. In today’s dynamic CX landscape, genuine human connection reigns supreme. Forget numbers and algorithms; it’s about listening deeply, responding with empathy, and building lasting relationships that transcend fleeting transactions.

In this article, we delve beyond traditional metrics and explore the human-centric pillars of CX excellence:

• Championing the customer voice: Ensuring their needs and concerns are heard loud and clear.
• Aligning business goals with customer needs: Making their satisfaction the true driver of success.
• Cultivating a collaborative spirit: Breaking down silos and fostering a unified CX vision.
• Embracing continual evolution: Adapting to changing customer expectations and market trends.
  

Prepare to reimagine your customer interactions and unlock the transformative power of genuine human connection. The ever-evolving world of CX awaits, and the path to lasting relationships starts with one simple truth: people matter most.

“In the ever-evolving landscape of customer experience, our compass isn’t just data or trends; it’s the genuine human connections we forge. At the heart of every strategy and innovation lies a simple truth – when we listen closely to our customers and respond with empathy and agility, we build lasting relationships, not just better experiences. That’s the true north of Customer Experience excellence.” 

Blending Roles in CX Work

In my journey as a CX Champion, Problem Solver, and Influencer, I’ve realized these roles are interconnected like gears in a well-oiled machine. As a Champion, I advocate for CX’s pivotal role in business success. This advocacy lays the groundwork for my problem-solving, where I tackle specific CX challenges. Influencing comes naturally as I share these solutions and insights with the broader community. It’s about continuously learning, applying, and sharing – a cycle that keeps the CX world spinning.

Also Read: 5 UX Trends to Watch This Year

Moving Beyond Traditional Metrics

Companies often rely on metrics like Net Promoter Score (NPS) or Customer Satisfaction (CSAT). While important, they don’t always paint the full picture. To truly gauge CX’s impact, we must look at customer lifetime value, retention rates, and employee engagement levels. For instance, a study by Bain & Company shows that increasing customer retention rates by just 5% can increase profits by 25% to 95%. Companies should embrace a holistic view of metrics, connecting customer behavior and feedback directly to business outcomes.

Common Pitfalls in Building a Customer-Centric Culture

One major pitfall is viewing customer-centricity as a departmental function rather than a company-wide ethos. This narrow approach can lead to disjointed customer experiences. Another pitfall is not adequately investing in employee training and development. Employees are the frontline ambassadors of your CX vision. Without their full understanding and engagement, even the best-laid plans can falter.

Key Steps for Tackling Complex CX Challenges

Firstly, understand your customers deeply through data and feedback. Then, align your business objectives with customer needs. Implement a cross-functional team approach to ensure all departments contribute to the CX vision. Regularly review and adapt your strategies based on customer feedback and market trends. Remember, a successful CX strategy is not set in stone; it evolves as your customers do. Here’s a comprehensive guide:

• Deeply Understand Your Customer:
• Gather Data: Collect data from various touchpoints – surveys, social media, customer service interactions, and purchase history.
• Analyze Feedback: Look for patterns, preferences, and pain points in the feedback. Use qualitative and quantitative methods for a comprehensive understanding.
• Create Personas: Develop customer personas to represent different segments of your audience, helping to tailor experiences to specific needs.
  
• Align Business Objectives with Customer Needs:
• Review Business Goals: Ensure your business goals consider customer satisfaction and loyalty.
• Integrate Insights: Use customer data to inform business strategies, ensuring they meet customer expectations and solve problems.
• Communicate Objectives: Communicate how aligning with customer needs will drive business success to all stakeholders.
  
• Implement a Cross-Functional Team Approach:
• Form Diverse Teams: Include members from different departments (marketing, sales, customer service, product development) in CX initiatives.
• Encourage Collaboration: Foster a culture of collaboration with regular meetings and shared platforms for communication.
• Set Shared Goals: Establish common objectives for these teams to improve CX.
  
• Regularly Review and Adapt Your Strategies:
• Monitor Feedback: Continuously track customer feedback and satisfaction metrics.
• Stay Updated with Market Trends: Keep an eye on industry trends and competitor strategies.
• Be Flexible: Be ready to adapt your strategies based on new insights or changes in the market.
  
• Remember the Evolutionary Nature of CX Strategy:
• Embrace Change: Acknowledge that customer preferences and market conditions will evolve.
• Iterate Constantly: Regularly revisit and refine your CX strategy to stay relevant and effective.
• Encourage Innovation: Promote a culture where new ideas for enhancing CX are always welcomed and explored.

Bridging EX and CX

Companies like Southwest Airlines and Salesforce have excelled at linking EX with CX. They focus on creating a positive work environment and culture that empowers employees, which, in turn, reflects in their customer interactions. Salesforce, for example, boasts high employee satisfaction rates, which correlate with its reputation for exceptional customer service. The key is understanding that happy, engaged employees naturally lead to happy, satisfied customers.

Breaking Down Silos for Collaborative CX

Leaders must foster a culture of open communication and collaboration. Encouraging cross-departmental projects, shared goals, and regular inter-departmental meetings can help. It’s also about ensuring everyone understands the common CX vision and how their role contributes to it. A McKinsey study found that companies with strong cross-functional collaboration are 1.5 times more likely to report revenue growth of 10% or more.

Also Read: AI Transforms Employee Experience, Driving Customer Success

Building an Agile CX Strategy

An agile CX strategy is all about responsiveness and flexibility. It involves continuously monitoring customer feedback, market trends, and internal performance metrics. Companies must be willing to pivot quickly based on these insights. This could mean adjusting policies, retraining staff, or even overhauling a service channel. Agility also means being innovative and open to experimenting with new approaches to enhance customer experiences.

The post Building Lasting Customer Relationships in the Humanized Age of CX appeared first on MartechView.

Within the survey approaches, you may develop a variety of sorts, such as a general feedback survey or a Net Promoter Score survey. Each focuses on a different part of your customers’ experiences, yet they all try to comprehend their feelings.

What is a customer effort score (CES)?

A service statistic called the Customer Effort Score (CES) measures customers’ efforts to connect with your organization. These encounters might involve how difficult it is for them to utilize your product or service or how simple it is to address a problem with your customer care representatives.

If consumers need to browse several knowledge-based articles to get the one they need, they will spend a lot of work. Still, they will spend less effort if they can phone a service representative and have their refund completed immediately.

There is ample proof that a particular experience’s simplicity is sometimes a more significant predictor of client loyalty than merely gauging consumer happiness. Additionally, customer loyalty is an absolute cornerstone of successful companies in an increasingly competitive market.

Because of this, CES is well-liked by customer success teams. You ask the buyer to rate the convenience of their experience rather than how delighted they are.

With the publication of an HBR article titled Stop Trying to Delight Your Customers in 2010, the Customer Effort Score gained prominence. The essay is instructive—if not for the high caliber and breadth of the study, then at least for the surprising conclusion: The most straightforward approach to developing customer loyalty is not impressing your consumers but making it simpler for them to accomplish their goals.

When to use customer effort score

Knowing when to utilize CES surveys is crucial since it may hugely influence success to know how much effort customers make to engage with your company.

Following a transaction or subscription-related contact

A smart approach to get information on how much a client puts into completing their purchase is to send them a CES survey after they have engaged with your company and ultimately made a purchase.

They will have just completed an action, so the details you requested are still fresh in their minds. For instance, set it up so that, as clients reach the page confirming that their transaction has been processed, a poll cleverly asks them about their overall experience.

CES is often assessed by sending consumers an automated post-interaction survey asking them to score a specific statement on a set scale, depending on the interaction they just finished.

Also Read: Beyond NPS: Why Customer Feedback Needs a 360-Degree Revolution

Immediately after your customer service team or any other service-related encounter is finished

Sending surveys at any regular frequency makes little sense because CES surveys expressly ask consumers to assess the amount of effort they put into alleviating a pain issue.

Instead, businesses will send them immediately following a customer care interaction, such as after an email support case is handled or after a service-related experience, like reading a knowledge base article, to see how successful it was in fixing the issue.

Customers who have to call your company for troubleshooting should instantly receive CES questionnaires when their problem has been fixed. This will determine how hard they tried to contact you for a solution.

To supplement product teams’ UI and UX testing

The overlap between product and customer success teams’ use of the Customer Effort Score (CES) is intriguing. Product teams are starting to utilize CES to obtain feedback on how effectively the UI supports new feature uptake and pinpoint instances where consumers feel confused and lost.

There are two ways to present your CES surveys.

Likert Scale

A Likert Scale is a numerical rating scale with five to seven points corresponding to pertinent terms like “very tough” or “extremely easy.” Higher numbers indicate greater work, whereas lower numbers indicate relatively easy/low effort. 

The survey’s instructions for Likert Scale questions that occasionally contain numbers inform customers of the possible range of answers. 

Emoticon Ratings

Although emoticon ratings are less common than Likert Scales, they are nonetheless useful indicators for consumers since they allow them to connect effort level to cheerful or sad expressions. 

Regardless of your approach, it’s crucial to remember that the questions you use should be unique to the aspect of the organization you’re trying to examine. The query should be focused on that contact, for instance, if you want to know how much work goes into opening a customer support ticket.

Customers can also be asked open-ended questions after giving their first response to help them understand why they gave a particular score.

You should know your average score after a sizable number of survey replies. Let’s discuss how you can determine your CES score.

Customer Effort Score Calculation

Your customer effort score is determined by multiplying the total number of survey replies by the sum of all customer effort ratings. The outcome will show you the typical level of effort clients make while dealing with your company.

Customer Effort Score = (sum of customer effort ratings/ Total number of survey responses)

The procedure is slightly different if you’re utilizing emoticons. For your internal analysis, you should give each emoticon a unique number. For instance, you may connect three to a sad face and one to a happy face. The greater figure represents the average amount of effort made by your consumers. You would next compute the average number of persons who chose each face.

Also Read: Building Lasting Customer Relationships in the Humanized Age of CX

What is a good customer effort score?

There is no unambiguous industry standard for customer effort scores. Nevertheless, based on how you set up your survey scales, average effort ratings that tilt more in one of the two directions show where your company is in terms of customer experience.

If your scale, for instance, rates one as low work and seven as substantial effort, a score of three indicates that consumers aren’t facing any major obstacles. Six, on the other hand, signifies frequent customer difficulty.

Your CES provides important data for analyzing usability and overall experience. Despite your best efforts, however, it does not tell you how pleased your consumers are with your company. Before launching your first CES survey, you should be familiar with all of the benefits and restrictions of this statistic.

A Customer Effort Score provides a robust measure because it lets you know how simple it is for consumers to connect with your company. This is probably your desired aim since you want to simplify their lives.

There is no customer feedback survey whose responses give you all the necessary information. Choose the best option after determining what is appropriate for your company and the information you need.

The post All You Need To Know: Customer Effort Score (CES) appeared first on MartechView.

It’s no secret that advertisers and publishers alike are under immense pressure regarding how they accurately measure and report the success of their online campaigns. No longer looking exclusively at views or clicks, they are demanding more quality measures of engagement tied directly to business outcomes. This has precipitated a growing and conspicuous move toward more valuable metrics. In particular, attention. 

Over the past few years, the industry has been enthusiastic about attention measurement. If done meaningfully by demonstrating real interest and personal investment in a brand, attention can benefit nearly all actors within the advertising ecosystem. This includes creative teams making more deterministically impactful ads, media agencies deploying budgets more efficiently, and large and small publishers maximizing their brand investment and valuing their inventory. Everybody stands to gain. 

It’s perhaps unsurprising then that this buzz has led to another long-standing industry echo chamber. Arguably, the race is on to develop industry-standard attention metrics, which has resulted in significant variance in interpretations of attention. While these measurements are not without merit, existing metrics fail to capture the full essence of attention. This is reflected in a resistance to move from impressions to attention. If a competent and transparent attention metric is not devised soon, the lack of clarity surrounding attention threatens to undermine its whole value.

Given these high stakes, all constituencies must rally around educating and disseminating technical expertise attention to promptly and effectively seize the opportunity it presents. 

Also Read: All You Need To Know: Customer Effort Score (CES)

Come together right now

The recently created IAB Attention Council Task Force is vital in this regard. It is dedicated to understanding what advertisers and publishers are looking to solve and how various attention solutions can achieve that. 

Producing best practices and technical guides concerning diverse approaches to measuring attention, the Task Force is delving into the solutions offered and providing crucial education on how marketers and publishers can effectively harness these solutions. However, ensuring that the measurement is tied to quality outcomes requires an understanding of how consumers engage with digital content at a level of granularity not previously seen, i.e., asking questions such as: “How much time has the user spent within the action areas of the ad?” and “Was the sound playing?” 

The best attention metrics will combine customer interactions and advanced Machine Learning techniques and optimize toward an attention metric to deliver the best possible result. Taking a step further, the most powerful attention solutions will be those that can view attention metrics derived from a very broad range of factors. These include bidding, publisher inventory, audience profiles, and the data directly associated with consumer actions. 

Indeed, technology is underpinning the path to a clear and widely palatable measure of attention. Creatives will, therefore, have to accept technology’s assistance in moving forward with attention. This may sound ominous to some in the industry – yet the reality is that creativity, having taken a backseat in the third-party cookie era, is about to take center stage again, thanks to the creative intelligence at its disposal. This data-led standard of attention finally offers the industry a way to effectively bridge the art and science of advertising.

What happens now is a really big deal

Attention could emerge as the most important thing we as an industry collectively track—if done correctly. A properly conceived and designed standard of attention, led by data science and AI, will yield better execution and results and dissolve the reluctance currently exhibited by some bodies towards it. 

Access to actionable real-time attention data will be immensely valuable to brands, agencies, and smaller publishers. For example, as brands look to translate engagement into profit, the digital environments outside the walled gardens—where consumers still spend excessive time—will be well-placed to recapture more value. More importantly, it’s a chance to better the whole ecosystem and start serving ads optimized toward interaction that doesn’t frustrate the user but engages them. 

Also Read: Mastering LTV: Data Analytics and Attribution

That’s why leaders across the industry need to move fast, pushing for collective action and rapid development of the methodology and grounded research. While the IAB Attention Council Task Force spearheads the movement, it requires investment across the entire ecosystem to quantify and architect the right attention metric. Providing there is a collective focus on attention, I’m confident it will finally deliver on its promise, and every player in the space will be a winner. 

The post Why Attention Metrics Matter in 2024 appeared first on MartechView.

Planning early for peak season campaigns like White Friday and utilizing remarketing strategies can further enhance user acquisition and engagement. It’s not just a wise opinion but an important takeaway from a recent ecommerce report by AppsFlyer. 

“Organize user acquisition campaigns ahead of White Friday and Single’s Day to benefit from the more affordable costs during this timeframe, and use remarketing strategies to guide users to the app via paid and owned media channels,” said Sue Azari, ecommerce industry consultant, AppsFlyer. Martechvibe spoke to her about the growth of mobile commerce despite the inflation and the consequential strategic shift in the mobile industry.

The conversation was necessary due to the increased mobile usage in the last few years. Moreover, the increasing availability of diverse products and services has compelled brands to prioritize mobile commerce. This shift has enabled users to conveniently access and purchase items on the go, putting the power of shopping at their fingertips whenever needed.

In response to the rise of mobile commerce, ecommerce mobile apps provide users with an enhanced shopping experience by incorporating intuitive interfaces, personalized recommendations, and seamless navigation. As a result, the overall process of shopping becomes more streamlined and enjoyable for users. However, ad fraud remains a challenge, and effective measures are being taken to combat it. 

Here are four learnings from Azari.

The rise of fingertips engagement

The pandemic-accelerated rise of mobile, coupled with more products and services ever available, demand from shoppers has driven brands to emphasize mobile commerce, on-the-go and customer engagement at the user’s fingertips whenever the need to buy arises. 

“This enhanced usability has increased customer engagement and longer session durations. Mobile apps have also facilitated greater convenience and accessibility for customers. With features like saved payment information, one-click ordering, in-store navigation, and push notifications, apps have made it easier for customers to discover products, track orders, and receive personalized offers,” said Azari.

Fighting ad fraud

Digital advertising is less exciting for customers than it is for mobile ad marketing fraudsters. Over the years, multi-billion dollars have been invested in digital advertising, and cases of ad fraud and scams are sporadically on the rise and dynamic. Nevertheless, several platforms and tools are being developed to keep fraud at bay.

For instance, Appsflyer claims to keep app marketers ahead of every threat and their marketing budget safe through a real-time, multi-layered approach that includes cluster analysis, personalized validation rules, in-app fraud rules, and post-attribution fraud detection. 

“Fraudsters attack budgets in the ecommerce sector using the same methods as in other industries, and the larger the budgets, the more interesting they are for attacks. We observe that ecommerce players are predominantly focusing on payment fraud – and neglecting ad fraud as a threat,” added Azari.

Data Analytics & Attribution Duo

“Connecting the dots between these different touchpoints and ensuring you’ve linked the right data to your app — can be a real challenge,” said Azari.  

A shopping consumer’s journey frequently involves multiple devices, platforms, and channels, encompassing both online and offline ad exposure and various touchpoints. For example, a single purchase may begin in a physical store, followed by further research on the web, and eventually result in a purchase made through a mobile app. This illustrates how consumers navigate different stages and channels during their shopping process.

“Working with an effective attribution and measurement provider can help bridge the gap to significantly improve the user experience, attribute marketing’s contribution, and ultimately increase your LTV. By measuring performance, analyzing user behavior, employing attribution modeling, conducting A/B testing, and personalizing marketing efforts, businesses can make data-driven decisions to enhance user experiences, drive growth, and achieve their business goals in the competitive mobile app landscape.”

Finally, here’s a strategic tip.

To improve the effectiveness of your marketing campaigns, prioritize enhancing the user experience at every touchpoint, ranging from the app store to the checkout process. By doing so, you can improve conversion rates, encouraging more users to complete purchases and retention rates and ensuring that customers continue to engage with your brand over time.

“Leverage the power of data analytics and attribution to measure and analyze key metrics, such as customer acquisition costs, conversion rates, and customer lifetime value. This data-driven approach will enable you to identify areas for improvement, allocate resources effectively, and make informed decisions. Also embrace a diversified mix of marketing channels, and don’t be afraid to test new creatives or new channels,” said Azari.

The post Mastering LTV: Data Analytics and Attribution appeared first on MartechView.