Machine Learning for Retail.
Impact
your Stores. your Customers. your Brand. your Shopping Experience. your Operations. your Sales. your Security.

Your data is powerful. In-store channels such as Scan&Go enables you to collect previously unreachable data.

Data-driven Growth in Retail

Using Machine learning in retail has driven a large share of eCommerce growth in the past years. We have set our mission to bring the full power of data-driven solutions to the in-store shopping experience

Machine Learning models can be trained to analyze and recognize patterns in huge amounts of data, learning as they go, constantly improving. Applying these capabilities to the data you collect in your stores, that allows us to personalize and continuously improve the in-store shopping experience through every available channel. One of the key advantage of having a self-scanning solution is that you collect data previously unreachable; what is bought inside the store, when it is bought, and so much more. 

PLATFORM

Impact Cloud

Algorithms designed for physical retail stores consider behavioral differences between shoppers, individual consumption preferences and the store environment to improve efficiency in operations, drive sales and get access to a new level of business intelligence.

The complementary relationship of My-Scan™, My-iScan™ and the Impact Cloud enables us to solve a wide range of problems and continuously innovate the customer experience in-store.

INTELLIGENT PRODUCT RECOMMENDATIONS

Impact CX

powered by intouch.com

Truly relevant product recommendations combined with a non-invasive user interface drive sales and provide a helpful service to your customers. Powered by intouch.com, this machine learning-based recommendation engine is designed for physical retail environments!

Using the 1:1 communication channel of our My-Scan applications, impact CX enables retailers to promote truly relevant products at the optimal time and location in-store.

Use real-time behavioural data and consider factors such as; demographics, weather, store location, time of day, day of week etc. in order to decide what product to recommend and when.

Recommendations are displayed at the critical moment of truth.

 

Making the right decision, in real-time.

Product Intelligence

Understand what products are sold in-store and: Who buys them? When they are bought? What other products are they associated with?

Store Intelligence

What is happening in real time in and around the individual store: Is it raining outside? Is there traffic nearby? Is the store in an affluent area? Is there a big event (football game) happening tonight?

Customer Intelligence

Who is currently inside the store: Purchasing patterns? Demographics? What should be promoted if they buy a particular item?

Driving Sales, continuously:

Fully Automated

Save thousands of hours by eliminating rule-based engines and switching to fully automated product and event tagging.

Target Accurately

Continuous optimization by constant re-training of audience association models to create the world’s most accurate in-store targeting.

Responding in Real-Time

Deploy the cloud-trained models at edge-level to quickly interact with your dynamic store environments.

THEFT PREDICTION

Impact CTRL

Trust is good, control is better.

Leverage Machine Learning technology to control the impact theft on your business and revolutionize self-service theft prevention.

Impact Control identifies shopping patterns leading to theft on store-level and assigns an individual probability of theft to every self-service customer in the store. Theft probabilities are updated in real-time for every step of the customer journey!

Theft in Retail

Research conducted by ECR on 140 million self-service (Scan&Go and Self-Checkout) transactions from different stores & suppliers shows that the impact on retail losses has been underestimated for years.

 

%
of all transactions contained at least one error
out of 10 times a self-service transaction with over 100 items contains errors
%
Average higher shrinkage rate in stores with Scan&Go or Self-Checkouts
%
of the time shoppers with over 50 items made at least one error

Join our Early Adopter Program!

Contact us to have an impact on features, roadmap and more!

Is Artificial Intelligence the Answer to Improving the Self-Scanning Experience in Offline Retail Environments?

Is Artificial Intelligence the Answer to Improving the Self-Scanning Experience in Offline Retail Environments? More retailers are learning how machine learning algorithms can be used to maximize the return on their self-scanning solutions and optimize the scan-and-go shopping experience to match consumer expectations. by Your Edge Contributor, August 04, 2020As…