MDM Booster AI function
Personalized recommendations
Learning from the past, mistakes and successes in order to make well-founded recommendations – the AI-based association analysis of the MDM Booster supports you in securing this knowledge and automatically creating well-founded recommendations for more efficient business decisions, purchase recommendations for your customers or risk minimization.
- Sales strategies: Recommends products that are often bought together or are related in terms of time and region, for example (cross-selling and up-selling)
- Better customer approach: Supports personalized recommendations through Next Best Action (NBA) and Next Best Offer (NBO)
- Further training: Automated, individual recommendations for further training
Association analysis – recommendations
Association analysis is an AI-supported process that analyzes which elements frequently occur together in certain contexts, e.g. when shopping, in the course of a customer life cycle, logistics or training. Companies can use these findings to optimize product recommendations, make processes more efficient and support sales.
Example: An online store analyses purchase data and recognizes that customers under the age of 20 who buy a smartphone in April often also order a protective case and headphones. Based on this, personalized product recommendations are created that increase sales.
Sales potential
Companies are often faced with the challenge of optimally supporting their sales experts. Recommendations for a customer visit, individual offers or a discount offer, which are available to the sales employee within the CRM system, offer enormous sales potential. Unstructured, unrelated or difficult to interpret data makes it difficult to use the information within a CRM system and other data sources. Manual evaluations take a lot of time and are therefore available too late or not at all. A bitter loss for any company. Examples of the use of recommendations in sales include
- Personalized product recommendations for up- and cross-selling in e-commerce
- Sales campaigns that contribute to customer loyalty
- Recommendations for sales staff that take into account the entire company portfolio, regional and temporal contexts
Utilize the full potential of your sales force
- Efficiency: Maximize the efficiency of your sales professionals and minimize the analysis effort
- Maximum transparency: use AI for a clear, comprehensible and successful sales strategy
- Opportunity costs: Every decision in sales and marketing has its price - not only in the form of expenditure, but also through lost opportunities
Practical example: Personalized product recommendations in e-commerce
An online store for electronic goods wants to increase its sales through intelligent product recommendations. Until now, general bestsellers were suggested to customers, but there was no individual recommendation based on real purchase patterns.
The challenge
- Customers receive unsuitable or general product recommendations that do not meet their needs.
- The average basket value falls short of expectations.
- Traditional methods only offer limited optimization options for increasing sales
Solution: AI-supported recommendations
An individual AI model, trained with the MDM Booster, permanently evaluates all relevant information on visitors, current events, etc. Optimally matching, personalized product recommendations can be generated and provided in real time. Online sales increase by a factor of 3.8 within 6 months.
AI-supported association analysis enabled the online store to improve the conversion rate, increase sales per customer and create a personalized shopping experience.
Further examples of AI-based recommendations
Purchasing and sales data
Area of application: retail, e-commerce, marketing
- Shopping cart analysis
- Optimization of product placement
- Up- and cross-selling
- Identification of seasonal and regional correlations in the context of consumer behavior
Example:
A supermarket chain realizes that customers who buy bread often also buy butter or jam. The products are strategically placed together.
Customer behavior & personalization
Area of application: CRM, customer analysis, maintenance contracts
- Predicting which products or services are relevant for certain customer groups or customers.
- Recommendation of personalized offers based on previous interactions.
- Optimization of loyalty programs through the identification of preferred products.
Logistics & warehouse management
Area of application: Supply chain management, logistics optimization
- Recommendations for the incoming goods inspection of certain suppliers
- Identification of products that are often transported together
- Optimization of supply chains through recommendations for specific means of transport, drivers or sequences
Example:
A logistics company recognizes that certain goods are often shipped together and can therefore optimize the packaging and transport process.
MDM Booster
Intelligent pattern recognition and relationships
Use the MDM Booster to generate individual AI models for optimal recommendations for your processes, your customers and your sales, increase efficiency and always provide excellent customer service.
Automated recommendations with AI – easily and quickly integrated into your processes
Seamless integration into existing systems
Thanks to open interfaces, the MDM Booster can be easily integrated into existing MDM, ERP, PIM or CRM systems. Standard formats such as SQL, CSV, Excel, OpenAPI and S3 are supported, allowing companies to use their existing data directly for intelligent pattern analyses.
Individual AI models for customized forecasts
The MDM Booster enables the training of individual AI models, tailored to your company-specific requirements – without AI expertise. Maximize your process efficiency and exploit the full sales potential of your market.
With the AI-supported association analysis of the MDM Booster, our customers increase their efficiency every day, optimize their sales strategies and use valuable data for their long-term success.
Further use cases for AI-supported recommendations
Regional and temporal peculiarities significantly determine the investment behavior of your customers. We would be happy to support you in implementing your AI strategy in agricultural and agricultural technology.
Automatically identify potential buyers for the vehicle inventory, make optimal recommendations based on workshop information and prepare possible offers before a customer makes an official inquiry – increase customer satisfaction and your sales with individual AI models and the MDM Booster.
Based on the customer life cycle, family situation, socio-economic environment and many other parameters, you can generate optimal recommendations for your customers and prospects before they make inquiries to the competition.
Demo date
Interested in increasing sales? With the MDM Booster, companies receive powerful AI software that can be used to generate recommendations optimally for a wide range of use cases. We look forward to your appointment request!
Contact us
How can we provide support?
Would you like to receive further information or are you interested in an individual consultation? Simply let us know in a short message how we can help you and we will get back to you as soon as possible.
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