AI Isn't Killing Retail Jobs, Bad Schedules Are
AI Isn't Killing Retail Jobs, Bad Schedules Are
The Problem: Employee Turnover and the AI Narrative
Despite apparent stabilization in 2024, industry experts warn that by the end of 2025, retail industry turnover is expected to reach an all-time high due to massive layoffs (+274% increase), continued scheduling problems, and deteriorating working conditions that are driving unprecedented employee exits.
Companies like JCPenney and Forever 21 closed hundreds of locations, while craft retailer Joann filed for bankruptcy twice and closed all remaining stores. Macy's alone laid off roughly 2,350 employees and closed five stores as part of cost-cutting measures.
Companies needed to lay off people to ensure profitability, however, few conducted a full analysis on the impact. Some companies created bigger problems for their long-term sustainability. The problem is that the physical work did not go away – it created an unintended breaking point. The workload and resulting schedules from the pressures to complete the work are making more and more retail workers quit. Job insecurity is driving workers to other industries.
In this nightmare scenario – there are many companies that are doing it right. They are listening to their customers and employees and rapidly adjusting to the new realities. The proof is in their business results. Companies like Walmart and Costco have made significant strides to ensure better employee experience and better schedules.
We are quick to blame AI and rising uncertainty about AI. Is AI going to help our store customers? Let’s not forget, brick and mortar still contributes over 80% of all retail sales.
AI Has Ways to Go
News headlines trumpet the rise of self-checkout machines, AI-powered inventory systems, and chatbots handling customer service, instilling unfounded fears that AI is about replace humans everywhere. Let me burst a bubble or two: there is no AI in retail today, let alone one that is capable of taking a retail store job. Listen to your customers they are telling you about the problem - “there is no one to help me – when there is, they know less than I do about your brand and your product!”.
The issue isn’t some imagined implementation of AI in retail – there is no AI implementation in stores that will require a decrease in workforce. Corporate jobs maybe – but retailers are not Tech companies, despite what Wall Street may think.
The Numbers Tell the Story
The retail industry turnover rate sits at approximately 60-75% for hourly workers, putting it among the highest of all industries—well above the national average of 47%.
These aren't just statistics - they represent a human cost. A recent study found that 82% of retail workers reported increased levels of stress and burnout, with 40% experiencing high turnover in their organizations. The situation has become so severe that the quit rate for retail workers is more than 70% higher than in other US industries.
The Scheduling Crisis Hidden in Plain Sight
While layoffs grab headlines, the real damage is happening in the day-to-day scheduling practices that have made retail work unsustainable for millions of Americans. Fifty-five percent of retail employees surveyed reported suffering burnout in the past year, with mental health issues and worker shortages cited as top causes.
The problems start with basic unpredictability. Consider the cascading effects of a perfect storm to disengage any employee: They are scheduled for a "clopen" (closing one night, opening the next morning) allowing no rest with just 5-6 hours between shifts, they are assigned a last-minute weekend shift making them miss their child’s school play or anniversary, their shifts and hours change weekly making it impossible to plan their lives. These scheduling practices create discontent not just with the job but with the brand. Employees facing sudden and unplanned scheduling practices are 50% more likely to quit their jobs compared to employees who have stable schedules.
Beyond Individual Suffering: The Business Case for Change
The issue isn’t the Workforce Management system. Most of these systems come with built in tools to create great schedules. The problem lies in business processes. The very processes created to improve profitability can be the ones causing all the issues because the underlying assumptions have changed.
Poor scheduling doesn't just hurt workers—it devastates business performance. High turnover rates can hinder success and excellent customer service, disrupt service quality, add expenses to a business's bottom line, and impact overall workplace morale.
The financial impact is staggering. The Work Institute found that the cost of every trained employee resignation is 33% of their base salary. For a retailer with 100 employees earning $30,000 annually, that's potentially $1 million in turnover costs alone. Then there is the loss of sales. Trained employees know the product and services, know the customer, know the internal business processes. All that goes out the proverbial shop window at the detriment of great customer service. In some businesses, customers become loyal to their trusted advisor and go with them to a competitor.
Additionally, most hiring managers believe that employee turnover places a heavy burden on remaining employees, potentially damaging engagement, and morale. This creates a vicious cycle where over-worked remaining staff become more likely to quit, accelerating the turnover spiral.
The AI Red Herring
While the industry obsesses over AI disruption, the data reveals a different truth. A Resume Builder survey found that while 38% of companies plan to replace workers with AI in 2025, nearly four in 10 companies said they are likely to have layoffs for other reasons, with half citing anticipated recession concerns.
The irony is profound: AI is not replacing store teams anytime soon. The math looks great on paper, but it doesn’t work. The focus should on accepting the reality that we are the robot overlords are not coming anytime soon. Peopleless stores have not yet worked. Until that day, we need people and people needs good schedules. Let’s refocus our efforts - automation can actually help relieve burnout from worker shortages and increase productivity per worker, potentially allowing retailers to compensate employees proportionally.
How It Should Work
· Predictable Scheduling: Fair scheduling builds trust and helps meet legal requirements. Posting schedules at least two weeks in advance gives employees time to plan their lives, which improves job satisfaction and reliability.
· Employee Input: Involving employees in the scheduling process by soliciting their input and preferences increases employee satisfaction and fosters a sense of ownership and accountability.
· Work-Life Balance: employers need to increasingly prioritize flexible, employee-centered scheduling to support worker well-being and work-life balance.
· AI-Driven WFM Systems: Modern scheduling software can eliminate many common problems. Retailers using performance-based schedules see an increase in profitability per employee of up to 6% and an increase in customer satisfaction scores of up to 13%.
· Business Processes: Operational Excellence and Workforce Management go hand in hand. Properly implemented WFM and Operational Excellence can not only create better work environments but also directly impact both Conversion% and basket size leading to higher sales.
The Path Forward
The companies that will thrive in this new retail landscape are those that recognize scheduling as a strategic business advantage, not an administrative afterthought.
The business case is clear. Focus on your customers and your employees. Focus on Employee Schedules using modern WFM tools. AI has a long way to go before it can replace store teams. Use AI instead to help your store teams succeed.
AI Isn’t Killing Jobs, Bad Schedules Are.
he Problem: Employee Turnover and the AI Narrative
Despite apparent stabilization in 2024, industry experts warn that by the end of 2025, retail industry turnover is expected to reach an all-time high due to massive layoffs, continued scheduling problems, and deteriorating working conditions.
Companies like JCPenney and Forever 21 closed hundreds of locations, while craft retailer Joann filed for bankruptcy twice and closed all remaining stores. Companies needed to lay off people to ensure profitability, however, few conducted a full analysis on the impact. Some companies created bigger problems for their long-term sustainability. The problem is that the physical work did not go away, instead it created an unintended breaking point. The workload and resulting schedules from the pressures to complete the work are making more and more retail workers quit. Job insecurity due to constant layoffs is driving workers to other industries.
In this nightmare scenario – there are many companies that are doing it right. They are listening to their customers and employees and rapidly adjusting to the new realities. The proof is in their business results. Companies like Walmart and Costco have made significant strides to ensure better employee experience and better schedules.
We are quick to blame AI and rising uncertainty about AI. Is AI going to help our store customers? Let’s not forget, brick and mortar still contributes over 80% of all retail sales.
AI Has Ways to Go
News headlines trumpet the rise of self-checkout machines, AI-powered inventory systems, and chatbots handling customer service, instilling unfounded fears that AI is about replace humans everywhere. Let me burst a bubble or two: there is no AI in retail today, let alone one that is capable of taking a retail store job. Listen to your customers they are telling you about the problem - “there is no one to help me – when there is, they know less than I do about your brand and your product!”.
The issue isn’t some imagined implementation of AI in retail – there is no AI implementation in stores that will require a decrease in workforce. AI can do a lot but it still cant go get the blue shirt in a size small from the stockroom or make the customer feel cared for by developing a relationship as a trusted advisor.
Retail corporate jobs - maybe, but retailers are not Tech companies, despite what Wall Street may think.
The Numbers Tell the Story
The retail industry turnover rate sits at approximately 60-75% for hourly workers, putting it among the highest of all industries - well above the national average of 47%.
These aren't just statistics - they represent a human cost. A recent study found that 82% of retail workers reported increased levels of stress and burnout, with 40% experiencing high turnover in their organizations. The situation has become so severe that the quit rate for retail workers is more than 70% higher than in other US industries.
The Scheduling Crisis Hidden in Plain Sight
While layoffs grab headlines, the real damage is happening in the day-to-day scheduling practices that have made retail work unsustainable for millions of Americans. Fifty-five percent of retail employees surveyed reported suffering burnout in the past year, with mental health issues and worker shortages cited as top causes.
The problems start with basic unpredictability. Consider the cascading effects of a perfect storm to disengage any employee: They are scheduled for a "clopen" (closing one night, opening the next morning) allowing no rest with just 5-6 hours between shifts, they are assigned a last-minute weekend shift making them miss their child’s school play or anniversary, their shifts and hours change weekly making it impossible to plan their lives. These scheduling practices create discontent not just with the job but with the brand. Employees facing sudden and unplanned scheduling practices are 50% more likely to quit their jobs compared to employees who have stable schedules.
Beyond Individual Suffering: The Business Case for Change
The issue isn’t the Workforce Management system. Most of these systems come with built in tools to create great schedules. The problem lies in business processes. The very processes created to improve profitability can be the ones causing all the issues because the underlying assumptions have changed.
Poor scheduling doesn't just hurt workers - it devastates business performance. High turnover rates can hinder success and excellent customer service, disrupt service quality, add expenses to a business's bottom line, and impact overall workplace morale.
The financial impact is staggering. The Work Institute found that the cost of every trained employee resignation is 33% of their base salary. For a retailer with 100 employees earning $30,000 annually, that's potentially $1 million in turnover costs alone. Then there is the loss of sales. Trained employees know the product and services, know the customer, know the internal business processes. All that goes out the proverbial shop window at the detriment of great customer service. In some businesses, customers become loyal to their trusted advisor and go with them to a competitor.
Additionally, most hiring managers believe that employee turnover places a heavy burden on remaining employees, potentially damaging engagement, and morale. This creates a vicious cycle where over-worked remaining staff become more likely to quit, accelerating the turnover spiral.
The AI Red Herring
While the industry obsesses over AI disruption, the data reveals a different truth. A recent survey found that while 38% of companies plan to replace workers with AI in 2025, nearly four in 10 companies said they are likely to have layoffs for other reasons, with half citing anticipated recession concerns.
The irony is profound: AI is not replacing store teams anytime soon. The math looks great on paper, but it doesn’t work. The focus should on accepting the reality that our robot overlords are not coming anytime soon. People-less stores have not yet worked. Until that day, we need people and people need good schedules. Let’s refocus our efforts - automation can actually help relieve burnout from worker shortages and increase productivity per worker, potentially allowing retailers to compensate employees proportionally and prevent the turnover.
How It Should Work
· Predictable Scheduling: Fair scheduling builds trust and helps meet legal requirements. Posting schedules at least two weeks in advance gives employees time to plan their lives, which improves job satisfaction and reliability.
· Employee Input: Involving employees in the scheduling process by soliciting their input and preferences increases employee satisfaction and fosters a sense of ownership and accountability.
· Work-Life Balance: Employers need to increasingly prioritize flexible, employee-centered scheduling to support worker well-being and work-life balance.
· AI-Driven WFM Systems: Modern scheduling software can eliminate many common problems. Retailers using performance-based schedules see an increase in profitability per employee of up to 6% and an increase in customer satisfaction scores of up to 13%.
· Business Processes: Operational Excellence and Workforce Management go hand in hand. Properly implemented WFM and Operational Excellence can not only create better work environments but also directly impact both Conversion% and basket size leading to higher sales.
The Path Forward
The companies that will thrive in this new retail landscape are those that recognize Workforce Management and scheduling as a strategic business advantage, not an administrative afterthought.
The business case is clear. Focus on your customers and your employees. Focus on employee schedules using modern WFM tools. AI has a long way to go before it can replace store teams. Use AI instead to help your store teams succeed.
WFM Forecasting Best Practices: A Short Guide to Ensure Accurate Forecasts
1. Data Hygiene
a. Data Quality
· Inbound Data: Create processes to clean data which include removing/adjusting outliers caused by one-off events (e.g., system outages, promotions, cancellations, weather).
· Historical Data: Review all historical data. If there were issues with data quality at any given time period in the past, it may be impacting forecasts. Ensure data hygiene at every level.
· Integrations: Review what data the system is actually using and set up processes to validate that the integrations are bringing in accurate inbound data. The data seen by the forecasting engine may be different than the data shown on the BI tool. If you have outbound data going to other systems – as a system owner, ensure your outbound data is reaching other systems correctly.
· Channel Clarity: In retail, each type of retail channel – full price, outlet, online need their own Labor Standards. In Contact Centers, this translates to how the interaction happens - phone, chat, and email have different volumes and patterns – ensure inbound data for channels are ingested separately and attached to the right Labor standards.
· Validations: Run DAILY automated validations of inbound and system data. Create alerts based on set thresholds. Daily data may change at the end of the week – include in validation process if this occurs.
b. Data Quantity and Granularity
· Quantity: Use recommended amount of data time frame – may need to go beyond 12 months. Use as much as the system will allow – 2-3 years for better Year over Year trends.
· Granularity: Bring in data in 15-min (or 30-min) intervals allowing granular accuracy in forecasts. This can significantly improve forecast quality and resulting schedules.
2. Forecasting Processes
a. Forecasting Processes and Algorithms
· Forecasting Cadence: Yearly – create “Bottoms-up” labor cost forecasts to align with Finance’s “Top-down” budgeting. Adjust quarterly with reforecasts based on updated trends and profitability goals. Forecast weekly at 2-4 weeks-in-advance cadence aligning with company scheduling policies and state or local labor laws.
· Forecast Accuracy: Compare forecast vs. actual EVERY WEEK. Set forecast accuracy percentage targets. Identify root causes of variances and fine-tune models accordingly. Be granular in this review. Create reporting tools that monitor forecast accuracy by metric and in a granularity that delivers a clear understanding of how to improve results.
· Create Accountability and Transparency: Involve stakeholders in forecast reviews - business leaders, finance partners, and other stakeholders should participate in weekly calibration sessions. This creates self-accountability and transparency. It is collaborative and builds trust.
· Intra-day/Intra-week Reforecasting: Recalculate forecasts throughout the day/week based on live data (e.g., queue spikes, absenteeism). Create the ability to adjust forecasted models and maintain profitability during peak volume.
· Algorithms – Comprehensive Review of Forecast Outputs: Better WFM tools come with built-in forecasting algorithms that can refine their own results. However, It is crucial that the forecasting team understands what these algorithms do and what results they produce. The right algorithm for the right channel and data set can make a night and day difference. Have a business process in place to review the outputs of these forecasting algorithms.
b. Considerations
· Rolling averages and seasonal patterns: Apply moving averages, weighted historical data, and seasonality decomposition when and as needed.
· Incorporate external drivers: ADD marketing campaigns, weather, or product launches and market specific events.
· Incorporate flexible staffing models: Gig, part-time, or split shifts to better respond to forecast accuracy limits.
· Machine learning models: Use both internal and external AI tools to detect patterns and adjust forecasts when and if needed. Use predictive analytics from other systems to benchmark.
· RTM for Contact Centers: using integrated Real Time Management (RTM) tools enable proactive changes to schedules. This can provide insights to forecast variances as they happen.
· FUTURE Impacts to Forecasts: Monitor SLAs and backlog trends. Factor in how service goals and backlogs might shift future volume and handle time. Account for agent behavior patterns that impact customers e.g., high absenteeism on weekends, or shift preference trends. These are scheduling trends but they can cause variances to forecasted labor.
3. Execution
The following areas should also be reviewed. The problem may not be in the data or in the forecast or the labor standards. It could be in one of the other areas.
· Labor Standards – Accuracy: Accurate Labor Standards: Sometimes forecasts are excellent, but labor standards are incorrect. This results in incorrect labor and poor scheduling. Review the accuracy of labor standards. If dated – you may need a project to adjust/ revise the standards. Labor standards can change over time due to improved average agent skills, new technology, business process changes, changes in channel types, etc.
· Labor Standards – Integrity: Teams sometime change labor standards to adjust to budgets or come within an expected metric. This can have a serious and unexpected impact on the quality of the labor demand generated. Restrict any change to labor standards.
· Schedules: Review scheduling rules and configurations. Is the system actually creating schedules as expected? No matter how good the forecasts are, issues with the scheduling engine will variances.
· Manual Workarounds: Sometimes workarounds are created out of good intentions to deliver better results. Although they may have worked once, they can now be causing unintended issues. It is important to understand if at any phase of the Data Ingestion, Forecasting, Labor Generation or Scheduling process, a workaround was created and what impact is that “workaround” actually having on the results.
Traffic Counting - What you need to Know
I have implemented several traffic solutions in my career. Let me share with you some of my learnings. I am happy to discuss further if you are looking for expert consultations on this topic.
Whether you are implementing a traffic counting solution for the first time or upgrading your current solution, here are some key considerations.
1. Business Objectives
Business Case: Know what you are trying to achieve and create your business case: Are you trying to increase sales, improve conversion rates, optimize staffing, better allocate labor, improve your forecasts, AND measure marketing effectiveness?
KPIs: Align traffic counts with metrics like conversion%, average transaction value, and Average sales per footfall,
2. Technology Selection
Sensor type: There are a lot of options. Your use case will decide what works best. Cameras are the best but sometimes the older infrared light sensors may work well.
Accuracy and calibration: Ensure solution offers >95% accuracy and has mechanisms for adjusting to real-world conditions. Consider the Imputation* method being used. Who and what is being counted - groups when families shop together, children, pets, shadows, and air movements (happens more often than we think!)
Advanced capabilities: Look at solutions that can provide key insight to traffic flow such as heatmaps showing how customers behave once inside the store. This can be useful to make data-driven merchandising decisions.
3. Installation & Store Layout
Entry/exit point coverage: Place sensors at all customer entry points, including side entrances, escalators, and connected malls.
Internal Store Coverage: Place counters inside the store if you are looking for insights on customer behaviors e.g., which product/presentation are the "dwelling" in front of.
Mounting height and angles: For cameras and overhead sensors, ensure optimal height (usually 8–12 feet) and unobstructed views. Your traffic vendor will take care of this usually.
Lighting and environmental factors: Ensure lighting doesn’t interfere with sensors (e.g., glare on glass doors, poor lighting in vestibules).
4. Data Integration
Most solutions provide the ability to pull data as batch jobs or using their APIs. Store the traffic data centrally and push to your internal platforms or create direct integrations.
Look for intraday APIs - This is critical if you are reporting KPIs real time (or close to it):
POS integration: To calculate retail KPIs e.g., conversion rate (sales ÷ traffic).
WFM integration: To align labor scheduling with Traffic patterns. Traffic, when reviewed as big data - is highly predictable. Your WFM forecasts will be better if you include Traffic data.
Marketing analytics: Attribute traffic changes to campaigns or promotions.
5. Data Privacy & Compliance
Anonymity: Ensure compliance with privacy laws (e.g., GDPR, CCPA) by anonymizing video or tracking data. Discuss with your Legal Department.
Clear signage: Inform customers if video analytics or Wi-Fi tracking is used.
6. Operational Considerations
Staff exclusion: Ensure the system can filter out employees from the court, especially during opening/closing or breaks. There are privacy considerations- consult your Legal Department when making these decisions.
Regular maintenance: Schedule calibration, firmware updates, and sensor cleaning.
Exception handling: Have protocols for outages or unusual spikes (e.g., mall events or emergencies).
Imputations*: For systems that impute data - have a process to shut off/exclude counts when a store is closed.
7. Reporting & Insights
Real-time dashboards: For store managers and regional leads to view performance by hour/day/store/district/region/country or your internal market hierarchy.
Historical analytics: Identify trends, seasonality, and cross-location benchmarks.
Actionable alerts: Notify when footfall exceeds thresholds (for staffing, service, security).
8. Scalability and Cost
Cost per location: Hardware, installation, data storage, and ongoing support.
Multi-store consistency: Use the same platform across stores for standardized reporting.
Cloud-based vs. on-premises: Choose based on IT infrastructure and scalability goals.
Remember as always - Prioritize solving your business needs - not cost.
*Imputations - the assignment of a value by inference from historical values present in the dataset.
A Proven Set of Strategies to Improve Conversion
Did you know that Brick-and-mortar stores hold a MASSIVE advantage in conversion over online retail? Stores deliver an average conversion of 20-40% vs ecommerce delivering a mere 1.8-2.3%.
Despite that, any seasoned retailer will tell you that most stores leave money on the table every day. With modern highly accurate AI-powered people counters, and a well-executed strategy, conversion% can be significantly higher.
A mere 1% improvement in the conversion rate can deliver a 5% growth in sales.
Did you know that Brick-and-mortar stores hold a MASSIVE advantage in conversion over online retail? Stores deliver an average conversion of 20-40% vs ecommerce delivering a mere 1.8-2.3%.
Despite that, any seasoned retailer will tell you that most stores leave money on the table every day. With modern highly accurate AI-powered people counters, and a well-executed strategy, conversion% can be significantly higher.
I have worked in all sides of retail – from Big Box to Specialty, from flagship store manager to corporate director - and I would like to share what I have learned.
A mere 1% improvement in the conversion rate can deliver a 5% growth in sales.
Current conversion benchmarks reveal frequently untapped store potential:
· Brick-and-mortar conversion rates significantly outperform digital channels across all retail categories. Industry data from 2024-2025 shows standalone stores achieving conversion rates up to 40%, while mall locations average around 15% due to higher browsing traffic. These figures dwarf online conversion rates, which hover between 1.8-2.3% according to Salesforce Research.
· Category-specific performance varies dramatically. Publicly available data shows Beauty and makeup retailers lead with 2.3% online conversion rates, while apparel follows at 2.2%. However, the in-store experience shows dramatically different patterns - fitting room users convert at 67% rates, making them seven times more likely to purchase than browsers. This represents one of retail's most powerful conversion levers.
· The broader context reveals retail's resilience: Capitol One Shopping states - 81.6% of all U.S. retail sales dollars still come from brick-and-mortar stores, totaling $5.927 trillion in 2024. With 83.7% of retailers maintaining at least one physical location, the opportunity for conversion optimization remains enormous across the industry.
Online has impacted brick-and-mortar but physical stores are far from sick and dying.
Conversion is not just about greeting customers when they walk in – that helps but there is a lot more to it. Corporate leaders will often tell you that metrics such as Conversion %, and Basket size are mostly owned by the store team. This is not always true. For brick-and-mortar retailers ready to maximize their physical advantage, I will put together all the pieces of this jigsaw puzzle and show you how each piece fits the overall plan for both immediate wins and long-term competitive differentiation.
This set of strategies do not just increase Conversion but also improve basket size.
Let’s get into it!
STORE DESIGN DRIVES MEASURABLE RESULTS
· Store Layout
Strategic layout optimization can increase conversions by 5%+ through psychological principles that guide customer behavior. The "right-turn rule" capitalizes on the fact that 90% of customers turn right upon entering - positioning core offerings and promotional displays immediately to the right maximizes impact. Meanwhile, the decompression zone (first 10-15 feet inside entrance) should remain clear as customers mentally transition into shopping mode.
· Traffic Flow Engineering
Traffic flow engineering follows proven patterns. Grid layouts increase routine shopping efficiency by 15-20% for grocery and pharmacy stores, while free-flow layouts encourage 25% longer browsing time in fashion and lifestyle stores. The IKEA loop design ensures 95% product exposure compared to just 40% in poorly designed spaces.
That brings us to store signs and navigation. Have you been at your grocery store recently trying to figure out where they moved the gluten-free flour? This is a common situation for shoppers in every store. The more time they spend searching for directions, the less time they spend buying – they lower their UPT (Units Per Transaction). Reduce customer frustration and increase efficiency with clear directional signage combined with strategically placed navigation signs. Indoor signage and navigation aids increase retail space foot traffic, while wide entrances with transparency boost entry rates. These simple items reduce the cognitive load of shopping, allowing customers to focus on products rather than navigation.
· Lighting, Music, Ambiance and Climate
o Lighting can deliver quantifiable improvements. Eye-level product placement combined with optimal lighting increases purchase likelihood by 82%. Warm lighting boosts comfort product sales by 20%, while cool lighting works better for tech and professional items. Starbucks' LED retrofit achieved 25% energy reduction while improving light quality, demonstrating that efficiency and effectiveness align.
o Music and ambiance create measurable psychological effects. Groceries have used this knowledge since the 1982 Milliman study - slower music under 72 BPM increases shopping time by 38% and spending by 38%. Background music at 60-70 decibels enhances mood without distraction, while displays appealing to multiple senses increase sales by 17%.
o Even architectural elements matter - display fixtures with rounded corners versus sharp edges increased sales by 15% in controlled studies due to subconscious threat-avoidance responses.
o Proper climate control affects perceived comfort and reduces early exits. Natural materials, plants, and calming colors improve customer satisfaction scores, with wellness-focused design emerging as a 2025 trend.
The data is clear - comfortable customers spend 15-25% more time in the store increasing the potential to convert AND increase basket size.
MERCHANDISING CREATES PRODUCT APPEAL
· Visual Merchandising
Visual merchandising excellence drives 8 out of 10 buying decisions based on what shoppers see in-store. Professional visual merchandising investment delivers up to 300% ROI, while well-designed displays increase time spent in store by 20%. The strategic placement of high-margin products at chest-to-eye height maximizes profitability, while end-cap positioning makes products 60% more likely to be noticed.
· Cross Merchandising
Cross-merchandising creates powerful sales multipliers. Complementary product placement increases conversion by 22% according to McKinsey research. Social proof integration through "Popular online" or "People also purchased" signage can increase conversion by up to 270%. The psychology of choice also matters - minimalist displays with fewer products increase perceived value by 28%.
· Dynamic Merchandising
Seasonal and dynamic merchandising maintains relevance. Stores with seasonally changing displays see 14% more browsing time, while professional visual merchandising shows measurable improvements of 15-35% in sales. The key lies in balancing product exposure with cognitive simplicity - too many choices overwhelm customers, while too few can limit revenue potential.
Merchandising or strategic product presentation is the best marketing tool a store has.
TRAINED STAFF MULTIPLY SALES
· Dale Carnegie - Trusted Advisor
Many of us grew up in retail learning Dale Carnegie's relationship-first selling approach that positions salespeople as trusted advisors rather than product pushers. This methodology focuses on building credibility through powerful questions and active listening, with companies seeing average revenue increases of 8.4% year-over-year. The system's effectiveness stems from its emphasis on understanding customer problems rather than pushing products.
· Sandler Training – Low Pressure Approach
Those familiar with Sandler Training's consultative selling methodology know that their selling system puts salespeople in control of discovery through a low-pressure approach emphasizing mutual respect. This system integrates clinical psychology principles to break traditional sales stereotypes, focusing on continuous reinforcement rather than one-time training events. The approach has shown 50+ years of proven results across multiple industries.
· The Critical Impact of Training Over Time
Academic research reveals the massive impact of great training. Harvard Business Review studies show that U.S. companies spend over $15 billion annually on sales training, yet over one-third of firms do not train salespeople at all. Companies with effective coaching programs show 8.4% revenue increases, while training programs incorporating visuals show 65% better retention rates. The key is spaced learning - small doses with frequent cadence show 17% more efficiency than traditional approaches.
Well-trained sales teams can drastically improve customer satisfaction and sales results.
CUSTOMER PERCEPTIONS SEAL THE DEAL
· Fitting Room Service
Your customers expect service while shopping, but they demand it in the fitting rooms.
Some retailers understand very well that fitting room service is the highest-leverage conversion opportunity. You can see this focus the moment you enter their fitting rooms. Service here is critical. Customers using fitting rooms are seven times more likely to purchase than browsers. There is clear data that shows 67% of fitting room users make a purchase. The multiplier effect is dramatic - customers receiving fitting room service are three times more likely to buy. It is also interesting that fitting room users have 50% lower return rates.
· A Story is Better Than a Thousand Greetings
Research from MIT Sloan reveals that 95% of cognition occurs in the subconscious, emotional brain. This means emotional triggers bypass logical evaluation processes, making storytelling and sensory experiences crucial for conversion. Stories activate multiple brain regions associated with sensory experience, creating deeper engagement than pure feature presentations. Instore marketing collaterals should strongly connect to the Brand’s/Product’s story.
· Social Credibility and Endorsements
Social proof mechanisms build trust and momentum. Customer testimonials and reviews create credibility, while "Others are buying" notifications generate fear of missing out. User-generated content increases engagement significantly, with influencer endorsements expanding credibility reach. The psychology of social validation drives purchasing behavior more powerfully than traditional advertising.
Endorsements that the customer trusts, whether that is a social media influencer or a celebrity or a trusted organization bring in already converted customers to the store.
These endorsements increase conversion likelihood substantially by motivating the buyer and reducing their purchase anxiety.
· Reciprocity
The reciprocity principle works through free samples - Sephora's sampling strategy encourages future purchases by creating a sense of obligation. These samples build demand over time.
Perception is reality – paying close attention to how your brand is perceived is critical.
TECHNOLOGY PROVIDES THE COMPETITIVE EDGE
· AI-powered Analytics Platforms
There are many examples if AI powered platforms revolutionizing retail – one being RetailNext's Traffic 3.0 platform that can track entire customer journeys. Using that data a well-known men’s clothing retailer is said to have achieved a 6.9% increase in conversion. These systems provide real-time occupancy tracking, customer journey mapping, and predictive traffic trends that enable dynamic staffing and layout adjustments.
· Heat Mapping and Customer Flow
The data reveals hidden optimization opportunities. AI optimized cameras analyze customer movement patterns, while Wi-Fi and Bluetooth (used by 72% of U.S. consumers) provide detailed behavioral insights. Sephora is said to have achieved a 30% increase in sales of specific promoted products through targeted offers based on customer location and behavior data coming from new technology.
· Point-of-sale Systems Evolution
Going from clunky and bulky registers with legacy software to sleek modern equipment powered by flexible and lighter AI-powered technology is creating an industry transformation. Cloud-based systems now command 68% of operator preferences, while 61% of retailers currently use AI in their businesses. Integration capabilities drive functionality for 85% of operators, with mobile POS solutions planned by 50% of restaurant operators. These systems provide the data foundation for conversion optimization efforts.
· Emerging Technologies
Augmented Reality (AR) and Virtual Reality (VR) create new conversion opportunities. AR in retail is projected to reach $61.3 billion by 2031, with beauty brands like Sephora using virtual try-on technology to increase customer confidence. IKEA's AR app allows furniture placement visualization, while TOMS used VR in 100 stores to showcase social impact, creating emotional connections with customers.
A contextualized metric such as Conversion needs accurate traffic counts. To take advantage of actionable traffic-related analytics, you need an accurate AI-powered traffic counting platform.
EFFICIENT CHECKOUT RETAINS SALES
· Friction reduction
Over time, the number of things we have added at checkout has come back to haunt us: Enter your zip code; your email; your phone number; agree to marketing promotions; join a loyalty program; open another unwanted credit card; how do you want this receipt; confirm your details… Although most transactions take about 3 minutes or less at the cash register, some retailers’ need to gather customer data has pushed this time up to the point where it’s inconvenient to the shopper.
From online transactions we know that 24% of cart abandonments come from customers who are forced to register for an account. In is inconvenient and time-consuming. A “Guest Checkout” option increases online conversion chances by 45%.
There is a lesson to be learned here. In a brick-and-mortar store, there is a correlation between the time it takes to check out and the frequency of the customer returning to that store to shop. In the age of Ecommerce competitions, longer checkout times or too many questions at the register create a psychological reluctance for the customer.
o Whitestuff.com’s redesigned checkout delivered a 37% conversion increase and 26% higher average order value.
o Walmart Canada's redesign of its mobile app increased conversions by 20%
o Soccerloco's visual cart design improvements led to a 26% revenue lift.
These examples demonstrate that checkout optimization impact conversion. To get back market share, Brick-and-mortar stores need to learn from these examples and introduce handheld POS devices, quicker transaction processing, alternate data collection methods, Amazon-type automatic ring up in the cart and more – all to make checkout experience significantly smoother.
Easier, faster, and pleasantly memorable checkouts matter. This is the last point of the in-store customer journey. This is what they will remember the most.
WFM IS THE BEST SALES SUPPORT TOOL
· Staffing to Traffic Patterns
Strategic Workforce Management, specifically staffing optimization, can increase conversion rates by 15-30% through intelligent scheduling that matches staff expertise and shifts with customer traffic patterns. Effective workforce management goes beyond simply having enough people on the floor – it's about having the right people with the right skills at the right times to maximize every customer interaction.
· Data Driven Results
Data-driven scheduling transforms conversion performance. Retailers using analytics-based workforce management see 20% improvements in customer satisfaction scores and corresponding conversion increases. By analyzing historical traffic patterns, seasonal trends, and individual associate performance data, managers can deploy high-converting staff during peak opportunities while ensuring adequate coverage during slower periods.
· Balancing Labor Cost
Labor cost optimization without sacrificing conversion. Advanced workforce management systems identify the minimum staffing levels needed to maintain conversion performance, preventing both understaffing (which hurts sales) and overstaffing (which erodes margins). The optimal balance typically involves higher staffing during peak conversion hours and streamlined coverage during low-traffic periods.
Successful retailers use workforce management as a strategic sales enhancing tool rather than just a scheduling or timekeeping application.
The retail landscape rewards retailers who understand that conversion optimization about creating experiences that acknowledge the customers purchase behavior and delivers what they want.