Saving Small Businesses with AI/ML

AI/ML to Generate Foot Traffic to Help Local Small Business

Let start with a mind blowing 🤯 fact!

Small businesses make up a staggering 99.9 percent of all businesses in the United States [US Chamber of Commerce]. This means that the vast majority of American companies are relatively small enterprises.

99.9 percent of all businesses in the United States

Yes 99.9% and how is life for small businesses?

The average lifespan of a small business in the US is around 8 and a half years, but there’s some variation in how this is measured. Here’s a breakdown:

• Survival Rates: Studies suggest that roughly a third of new businesses close within their first two years, and half are gone within five years [JPMorgan Chase Institute].
• Years in Operation: Looking at established businesses, around 51% are 10 years old or less, and 32% are 5 years old or less [JPMorgan Chase Institute].
• Business Closures: An estimated 550,000 small businesses close their doors each year [The Zebra].

That is brutal … how can we help?

Sample Around / Social Sample

It all started at a hack-a-thon in 2013 and now we are adding AI/ML

The check was larger than the amount.

Launch Conference Hackathon — 3.5.2013. This the genesis of the idea:

And now we add AI/ML.

Our solution builds on these two facts:

• We know that local shops live and die by foot traffic.
• And 90% of shoppers are more likely to make a purchase after an employee offers assistance.

The local store is the heart of the community

Foot traffic is crucial for local mom-and-pop shops as it directly impacts their sales and sustainability. High foot traffic leads to increased customer visits, greater sales opportunities, and improved brand visibility. These small businesses often rely on a steady stream of local customers for their revenue, as they typically lack the marketing budget and online presence of larger retailers. Foot traffic also fosters community engagement and loyalty, which are vital for the long-term success of these businesses. Without sufficient foot traffic, many mom-and-pop shops struggle to survive.

Foot traffic is very important for mom-and-pop shops:

• Sales and Revenue: More customers browsing the store translates to more potential sales, which is crucial for a small business with less financial buffer than larger chains.
• Customer Connection: Physical stores allow for personalized interactions with customers, which can build trust and loyalty. This can turn a one-time buyer into a repeat customer.
• Brand Awareness: Foot traffic creates visibility for the shop. People walking by might not be looking to buy something that day, but seeing the store can plant a seed and make them more likely to come back in the future or recommend it to others.
• Understanding Customer Needs: Observing customers in the store allows the shop owner to see what products are popular and what gaps there might be in their inventory. This can inform their future buying decisions.

Lets stop off and sample something

Summary:
- Foot traffic is vital for local mom-and-pop shops as it significantly influences their sales and sustainability. High foot traffic boosts customer visits, sales opportunities, and brand visibility. These small businesses depend on local customers, lacking the extensive marketing and online presence of larger retailers. Foot traffic also fosters community engagement and customer loyalty, essential for their long-term success.

Key points:
- Sales and Revenue: More customers lead to higher sales.
- Customer Connection: Personal interactions build trust and repeat business.
- Brand Awareness: Increases visibility and future customer visits.
- Customer Insights: Direct observation informs inventory decisions.

Foot traffic metrics are especially critical for monitoring and improving sales in retail environments like department stores and malls, which have been affected by e-commerce growth and the COVID-19 pandemic.

Where are we going next for our sample?

Solution: Give out Free Stuff!

Give Out Samples of Products.

Mobile app which shows a map of local shops providing samples of their products.

This drives foot traffic and allows local merchants to obtain real time feedback. For the first time brick and mortar stores can do A/B testing.

Shops with free samples of various products

Step One-List your store

Setup your store with what people will sample.

• On our website register your store information.
• Organize what people will sample (day/time/products)
• Create a feedback form & Coupon

People will be excited to see how their feedback improves the product making them personally invested in the business.

Customer Experience

Customers use our app to find your samples though our Android & iOS app.

Find the local business with samples.

Step Two — Set out samples and receive feedback

• Customers use our Android / iOS app to find what samples are available
• NFC tag / QR code to give feedback
• Receive instant coupon to use on the samples they like

Step Three — AI/ML builds a model of user preferences.

This deep ethnographic customer data will be used to train our AI/ML models to help all business to understand their customers and tastes.

Data Collection

1. User Interaction Data: Capture detailed interaction data from the app, such as which samples users select, their feedback on the samples, and coupon redemptions.
2. Demographic Information: Collect optional demographic data (age, gender, location) to enhance user profiles.
3. Behavioral Data: Track user behavior over time, noting repeat visits, browsing patterns, and preferences.

Data Processing

1. Data Cleaning: Ensure all collected data is accurate and free from inconsistencies. Handle missing values and outliers to prepare the data for analysis.
2. Data Normalization: Standardize the data to a common scale without distorting differences in the ranges of values.

Model Training

1. Feature Engineering: Extract relevant features from the data, such as user preferences, peak visiting times, and popular products.
2. Algorithm Selection: Choose appropriate machine learning algorithms (e.g., clustering for segmenting users, recommendation algorithms for suggesting products).
3. Training: Use the processed data to train AI/ML models. This involves splitting the data into training and testing sets, and iterating to improve accuracy.

Model Evaluation

1. Performance Metrics: Evaluate the models using metrics like accuracy, precision, recall, and F1 score.
2. Validation: Perform cross-validation to ensure the model generalizes well to unseen data.

Deployment

1. Integration with App: Integrate the trained models into the mobile app backend, allowing real-time recommendations and personalization.
2. Monitoring and Updating: Continuously monitor model performance and update periodically with new data to maintain accuracy and relevance
3. Product Improvement for Merchants: Provide merchants with insights derived from the AI/ML models to help them understand customer preferences and feedback. This information can guide them in refining their products, adjusting inventory, and improving overall customer satisfaction.

Benefits

1. Personalized Recommendations: Provide users with tailored sample suggestions based on their past preferences and behavior.
2. Enhanced Customer Insights: Offer businesses detailed insights into customer preferences, helping them stock products that are more likely to be popular.
3. Improved Customer Engagement: Increase customer satisfaction and loyalty by offering a personalized shopping experience.
4. Product Enhancement: Empower merchants with data-driven insights to improve their products, aligning with customer preferences and boosting sales.

Implementing AI/ML to generate foot traffic and enhance customer understanding marks a transformative step for local mom-and-pop shops. By harnessing user interaction data, demographic insights, and behavioral patterns, we can create sophisticated models that personalize customer experiences and provide actionable insights for merchants. This synergy not only drives foot traffic but also empowers businesses to refine their product offerings, ensuring alignment with customer preferences. As we move forward, the integration of AI/ML promises to sustain and elevate the vibrant ecosystem of local small businesses, fostering community engagement and long-term success.

We are excited to help grow your small business!

This approach not only enhances the user experience but also helps local businesses better understand and meet their customers’ needs, driving foot traffic and sales, while continuously improving their product offerings based on real-time feedback and data analysis.

Conclusion

leveraging AI/ML technologies to boost foot traffic and enhance customer insights represents a significant advancement for local mom-and-pop shops. By collecting and analyzing detailed customer data, our models can personalize user experiences and provide merchants with valuable feedback to improve their products. This innovative approach not only drives more customers to these stores but also helps small businesses thrive by aligning their offerings with consumer preferences. Embracing AI/ML is a pivotal step towards sustaining and growing the vital ecosystem of local small businesses, fostering deeper community connections and ensuring long-term success.

YLabZ & GNSeven

Executive Summery

The article emphasizes the critical role of foot traffic for the survival and success of small businesses. It highlights that small businesses make up 99.9% of all U.S. businesses but often struggle to survive, with many closing within a few years. To help these businesses, the article suggests using AI/ML to increase foot traffic, proposing an app that shows local shops offering free samples. This approach aims to drive customer visits, provide real-time feedback, and enable A/B testing for brick-and-mortar stores, ultimately boosting sales and customer loyalty.