6 Key Trends  are changing the Retail Landscape

Keepler can accompany you to boost each of them

Magic Point of Sale

Smartphones, apps, augmented reality, retailtainment… Consumers expect personalized and instantaneous shopping experiences. It is therefore necessary to adapt to new platforms and channels to meet their expectations. The magical point of sale must allow them to interact with a brand, search for products, try them out and shop in new and innovative ways. A deep understanding of customer culture and an easy and entertaining shopping experience are key.


The integration of the different sales and customer communication channels (physical stores, online stores, social networks, etc.) into a single seamless shopping experience. This is a strategy focused on providing an optimal shopping experience at any point of contact with the brand, allowing them to choose the channel that best suits their needs at all times, improving the relationship between the brand and the customer, their satisfaction and loyalty, and increasing sales.

Deep Retail

The use of advanced technologies is taking the retail sector to an inflection point, from just “looking” to actually “being” smart. The use of technologies such as artificial intelligence, big data or facial recognition technologies allows to personalize the sector to unsuspected limits: Know customers better than they know themselves. Knowing and leveraging all that information to improve their experience is no longer an option, it is a necessity to remain competitive.


Online stores continue to evolve and drive new ways of shopping and create new types of commerce where humans are no longer the only ones involved. A-commerce or “automated commerce” is a new way of shopping, where the customer can automate the buying process without having to re-engage in it. In this way, customers can schedule the regular purchase of certain products that they consume frequently in order to save time.

Quality Data vs for Big Data

Data is a crucial asset for retailers. Knowing a customer’s exact address to ensure successful product deliveries, understanding and predicting market and consumer trends to plan inventory, setting competitive pricing or personalizing their experience by providing accurate product recommendations is only possible with reliable and accurate data.

AI as a Reality

AI offers many benefits and advantages that can help retailers improve their operations and better serve their customers, enhancing the shopping experience and increasing sales through personalized recommendations, automating routine tasks, providing insights for better business decisions, making predictions for inventory and staffing, and enhancing security by detecting fraudulent activity.

To keep pace with rising consumer expectations, retailers and their brands must first make key investments to improve their backend operations.

A robust, data-rich infrastructure is needed to enable the collection, storage and processing of large amounts of information efficiently and securely.

Sophisticated analytics systems capable of extracting valuable insights and foster a business culture that prioritizes and encourages the use of data in the decision-making process.

Implement a cloud-based system to disseminate across the entire organization, from supply chain partners to front-line staff.

AI-based solutions for the retail sector

We help you revolutionize the retail industry paradigm with the power of AI

Client unique ID

We can help you build your unique customer view, aggregating different sources of information, both online and offline, around a unique anonymised customer ID, thereby understanding how customers interact with your brand across multiple channels and touchpoints, enabling you to create a seamless omnichannel experience and maximize offer personalization.

Personalisation & improvement of recommendation engine

Use customer insight and advanced analytics capabilities to impact with the most appropriate product at the most appropriate time for a conversion, reducing most worrying ratios for retailers, the risk of abandonment of sales processes, and finding the best next best action at any given moment to build customer loyalty.

Predictive Analytics

Using AI and Machine Learning Technology, retailers can use predictive algorithms to make more accurate sales forecasts by analyzing data on customer behavior, demand, and sales trends. By continuously training on new data, these algorithms can help retailers plan inventory and staffing more efficiently, as well as make better-informed decisions about pricing and promotions.

Unstructured data insights

Unstructured data can contribute to quality data by providing additional context and insights that may not be captured by structured data alone. For example, analyzing customer reviews and feedback on social media can help retailers understand their customers’ opinions and preferences, which can be used to improve products and services. This requires the use of advanced analytical tools such as natural language processing, machine learning, and sentiment analysis to transform unstructured data into structured data that can be easily analyzed and interpreted.

We help our clients transform their business through data

“They are a very solid team with serious knowledge of data science, algorithms, model training, and model scalability. They work with a high level of best practices in the field of development.”

- CTO, Retail Company -
Big Data

Customer Online Life-Cycle Modeling and Recommendation Engine

With several brands and e-commerce platforms, our client wanted to obtain an holistic and unified view of customers and sales in all brands. Using this information, the client wanted to increase online sales by targeting every customer with a personalized recommendation.

Big Data

Staff Optimization through Demand Forecasting

The brand plans to size the number of people needed to manage logistics processes based on the demand received and expected revenue in each country where it operates. Although this is a recurring need, it becomes more important during the festive season (Christmas) or sales.

Big Data

Look-to-book Ratio Reduction Through Customer Segmentation and White-lists

A Bedbank is a wholesaler of hotel rooms. Travel agencies browse room and hotel availability through the Bedbank application. The customer wanted to reduce the
volume of searches by recommending a personalized set of hotels to each customer.

Thinking about the future?

These are the goals for your business

Know your customers

As customers become more demanding and discerning, retailers must focus on delivering personalized experiences, understanding customer preferences, interests and behaviors, and tailoring the shopping experience accordingly across all channels.

Optimize operations

Optimize operations and create more agile and responsive supply chains to meet customer demand at scale by leveraging technology such as artificial intelligence, automation, and data analytics.

Accelerate innovation

Dynamize forward-looking business models, embrace new technologies and customer trends, and remain competitive in an ever-changing retail landscape.

Would you like to talk about your business?

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