BGA x Plato Webinar: AI-based Sales Optimization

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Thanks to the BGA for the opportunity to present concrete use cases of AI in wholesale distribution

The BGA represents the interests of wholesale and foreign trade and B2B service providers nationally and internationally and promotes an open, competitive and responsible economy. It was an honor to discuss the challenges of the current economic situation and the AI-based future of wholesale in front of this network. The BGA wants to introduce its members to innovative technology solutions such as Artificial Intelligence to make the industry more efficient and future-proof. We would like to thank the BGA for giving us as a company the opportunity to provide an outlook on AI in B2B sales and we greatly appreciated the exchange with the members of Germany's strongest wholesale network.

In order to make this knowledge accessible to other members of the BGA and wholesalers in general, we summarize the most important points.

Overview of the webinar:

1. Key findings of the webinar
2. Challenges in B2B sales
3. AI use cases in sales
4. Conclusion: AI to secure the future of wholesale

Key findings of the webinar:

1. Wholesale is ready for AI: Contrary to the common perception, there are no data hurdles. Companies have structured ERP data that represents decades of data treasures - ideal conditions for AI.
2. Use cases exist: Use cases such as churn alerts, up- & cross-selling or ERP automation have long been established, for example at Amazon. The task now is to implement these for B2B sales.
3. AI as the market standard: AI will become the standard in the market in the next 2-3 years, whereby, according to McKinsey, preparation for the turnaround and integration of AI by 2025 will determine who will be at the forefront.

The status quo in wholesale distribution

Technical wholesale is facing major challenges, worsened by difficult economic conditions and a shortage of skilled workers with a resulting loss of knowledge. A 40% drop in the BGA Wholesale Climate Indicator reveals long-neglected problems, particularly in the sector's currently still reactive sales. In order to remain competitive, companies must make their sales processes more efficient. 

‍The necessary change requires a strategic realignment and the use of modern technologies such as AI to automate administrative tasks and create more time for proactive sales and customer contact.

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AI use cases to make wholesale distribution more proactive

Churn alerts:

AI detects early signs of potential customer loss by analyzing purchasing behavior and reporting deviations. This enables sales to react proactively to retain customers and avoid a slump in sales.

Practical examples:

1. Sales analysis: Often used in wholesale, but not meaningful as sales losses reveal an already “sick patient” too late.
2. Partial churn: Monitoring of sales, e.g. based on product categories, in order to detect possible churn at an early stage.
3. Industry comparison: Comparisons of customer segments and their purchasing behavior in order to uncover declining purchases and gaps in demand. 

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Up- and cross-selling:

‍AI specifically identifies products that similar customers have purchased and suggests these to exploit sales potential. This optimizes the sales process, increases order value and strengthens customer loyalty.

Practical examples:

1. Category cross-selling: Uses sales history to identify similar customers who are not yet buying in a particular category.
2. Shopping basket completion: The algorithm recognizes which products match the customer's purchasing behavior.
3. Accessories & alternatives: Suggestions for similar or complementary products are optimized through reinforcement- and human-in-the-loop learning.

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Next best action:

AI suggests targeted next steps to sales reps to make the most of opportunities. It prioritizes open offers and detects anomalies to maximize sales success and strengthen customer relationships.

Practical examples:

1. First-time purchase: AI is used to send an automatic notification when a customer purchases products for the first time.
2. Prioritized offer tracking: Offers that have the highest probability of conversion are displayed to the employee.
3. Strong sales & margin change: AI recognizes anomalies in various sales metrics to ideally prepare the sales force.
4. Customer segmentation: Through targeted customer segmentation, the AI highlights those customers with the greatest potential. 

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Workflow automation:

AI automates the creation of quotations and orders, reduces manual tasks and optimizes visit planning. This allows sales staff to focus on sales and work more efficiently.

Practical examples:

1. Automatic offers & emails: Offers and emails can be automatically created using AI recommendations to treat even B and C as A customers.
2. Text-based order creation: Quotation and order proposals are automatically created from PDFs, emails, WhatsApp or GAEB files using generative AI.
3. Optimized visit & route planning: Based on the sales opportunities of all customers, ideal routes are calculated directly.
4. ERP interaction via chat: Searching in ERP via chat enables easy retrieval of data and completely new interactions via chat.

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Conclusion: AI to safeguard the future of wholesale

‍The use of AI in wholesale distribution is no longer an option, but a necessity. Companies that invest in AI now will secure decisive competitive advantages and lay the foundations for long-term growth. Innovative technologies such as AI in particular can overcome many of the current challenges in the market. Wholesalers who exploit this potential not only optimize their processes, but also strengthen their market position and sustainably increase customer satisfaction. Now is the time to start the change and shape the future of sales in wholesale with AI.

Contact us at benedikt.nolte@platoapp.ai to assess your specific situation with regard to AI solutions. We welcome criticism and suggestions on the topic and look forward to shaping the future of wholesale together with you.

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