Artificial Intelligence (AI) is fast on the rise and is becoming an integral part of our daily lives. No thanks in part to the global pandemic, its adoption across multiple industries will be greatly accelerated across various industries – medical, journalism, etc. 

Once it gains mass adoption in the B2B industry, what will this mean for wholesalers? 

Challenges Befalling A Wholesaler

As the wholesale distribution industry continues to evolve in complexity, many wholesalers have to perform a juggling act – finding the sweet spot between retailers haggling for lower prices and manufacturers aiming for a higher profit margin due to increasing commodity costs. 

But for a wholesaler, the two biggest factors keeping them up at night are poor scaling and the risk of disintermediation. 

Poor Scaling 

The ability to scale is crucial, but it is easier said than done. Higher-order volumes, expansion into new markets, and the introduction of new product lines compound the workload needed to keep things in order. 

Also, as scaling efforts increase, more warehouse space is occupied. 

This means that a wholesaler has to constantly evaluate their warehouse’s physical layout – determining the movement of goods and which areas are playing host to waste. Other factors include:

  • The team’s ability to keep up with a high influx of orders
  • The ease of making pickups 
  • The ability of pack stations and barcode scanners to cope with high volumes of orders efficiently

And one way to get around this is via the use of warehouse management systems. Advancements within the software have made them sophisticated enough to improve turnover, optimise warehouse space, and improve overall efficiency.


As retailers and manufacturers explore various ways to increase margins, it’s no surprise that wholesalers must adapt by providing value-added services, lest they be replaced. 

And that threat… is Dropshipping.

Source: Growtraffic

Dropshipping is when a seller accepts customer orders but does not keep goods sold in stock. I.e. No wholesaler. Instead, a store purchases the item from a third-party manufacturer to fulfill orders, shipping it directly to the buyer.

Due to minimal overhead costs, dropshippers are able to undercut wholesalers by fulfilling orders via large manufacturers. This buffer from its minimal overheads allows it to compensate for longer delivery times – up to weeks – by thinning margins. 

If you can’t beat them, join them. Or not. 

If you aren’t about to embrace the threat and welcome an opportunity for a partnership, another way is to market your offerings to potential customers in such a compelling manner that they dispel the need for dropshipping. 

With the help of artificial intelligence technologies, they introduce a greater level of optimisation and customisation through more intensive use and analysis of data which reduces the threats above. This allows wholesalers to capture their target audience with greater precision, providing more personalised offerings and streamlined operational processes.

More importantly, wholesalers can better differentiate themselves from the competition by demonstrating the value their services offer in terms of convenience, cost control, and customer fulfillment. 

And that’s where we form the case for AI adoption among wholesalers.

Source: Unsplash

How Can Artificial Intelligence Help? 

Despite the strong case for artificial intelligence in the e-commerce industry, the branches of AI – machine learning, natural linguistic programming, neural networks, etc. – are greatly under-utilised.

Many wholesalers are still performing their day to day tasks manually by relying on experience and instincts to guide their decision-making process. And this hesitation can be linked to a lack of resources, technical skills, or simply because it was never a top priority. 

This strategy may work in the short term, but it will hamper the scale of long term growth due to the inability to optimise pricing and sales – unnecessary monetary and temporal costs are incurred.

Using AI, wholesalers can automate their processes with increasing efficiency and productivity via:

Price, Bonus, and Discount Optimisation

With the help of elasticity forecasts, wholesalers can flexibly adjust their prices according to market dynamics. In terms of bonuses and discounts, machine learning allows specific bonuses to be applied to any customer-specific criteria.

Price Guidance 

Amazon has proven their hand at price recommendation using AI, as it contributed 35% of their revenue. Through precision pricing, Amazon is able to provide a tailored experience for every customer – no one will ever feel alienated. 

The same can be said from a wholesaler’s perspective. As high profit margins become harder to obtain, getting the most out of every customer becomes more crucial than ever. 

Demand Forecasting

Being able to accurately forecast demand development allows a wholesaler to optimise its inventory, product management, and pricing.

Customer Segmentation 

A profile of customers is created into segments via their unique characteristics, allowing for a highly group-oriented targeted approach.

Customer Lifetime Value Management 

By analysing customer purchase preferences and behaviour, wholesalers can easily retain customers, fulfilling their needs, and making more accurate predictions.

Improved Item Substitutions 

This feature significantly reduces the severity of stockouts caused by poor manufacturing processes, extended lead times, disorganised delivery, and poor planning. 

The use of AI will allow wholesalers to exert more control over their substitution strategy via the extraction of the correct data. Through the use of an AI-powered product substitution system, wholesalers are able to preserve their margins by automating processes, assigning them by customer profiles, and prioritising products to be substituted.

Even if AI is still a maturing technology, its potential to provide ongoing benefits via process automation, cognitive insights, and cognitive engagement will bring about positive changes for both wholesalers and buyers alike. 

Source: Information Age

Process Automation

Robotic Processing Automation Technologies (RPA) mimics human actions in inputting and consuming information from various IT systems. Typically used for automating digital and physical tasks, these tasks include: 

  • Reconciling failures to charge for orders across billing systems by extracting information from multiple documents 
  • Updating customer profiles according to the latest changes e.g. service additions or address changes. 

With RPA being the easiest system to implement, it is most suited for working with multiple backend systems. However, it is also one that holds the least processing power although developers are slowly adding more intelligence and learning capabilities.

Cognitive Insights

By using algorithms to analyse patterns and their relationships in large volumes of data, parts of data sets with a meaningful correlation are then utilised to train their models. This data-intensive approach allows wholesalers to yield insights far superior than traditional analytical methods. 

This is what they bring to the table:

  • Predicting customer purchase patterns 
  • Automating personalised targeting of ads and recommendations

What this means is that the data curation process becomes less labour intensive. Because these machine learning algorithms are built to recognise image and speech, they will be able to make new data available for better analytics. 

Cognitive Engagement

Via natural language processing chatbots, the aim is to use said technologies to deliver more personalised customer interactions such as:

  • Resolving customer service queries and issues. These range from addressing simple questions to technical support questions in the customer’s natural language.
  • Provide recommendations for retailers and increased personalisation.

AI – The Future For Wholesalers


Teething issues aside, artificial intelligence has the infinite potential to leave a positive dent on the wholesale landscape. 

Through the use of related technologies such as machine learning and natural language processing, wholesalers will be able to enhance the efficiency of their operational processes, thus allowing them to overcome any internal and external challenges they face by achieving an unprecedented level of optimisation.

This means customers can receive a premium experience, without wholesalers having to incur any additional costs. 

This gives them the agility to deal with unforeseeable changes in the future, because decision making and forecasting can be done more accurately with the abundance of new data, eventually leading to the development of new business models and revenue streams.

The future of artificial intelligence in e-commerce is promising, and as advancements continue to emerge with time, we expect a wider adoption across various industries. 

For businesses across Malaysia, Dropee is an e-commerce solutions provider that seeks to support our local B2B entities by providing them with a platform to help them streamline and manage their customers and inventories with efficiency and ease. We also help to connect businesses with one another via an online marketplace where they can reach out to more people in a fuss-free space.

To learn more about what we do, reach out to us for a free consultation with our team and get a headstart in digitising your business today!


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