There’s a lot of attention on how AI, machine learning, and big data are at the top of technology trends which are transforming the way business is done, particularly in the B2C landscape.
It’s not surprising to see there’s more focus on AI in regards to B2C companies than B2B – after all, the consumer base is significantly larger.
Through its profound effect on the customer experience, AI and machine learning are evolving the concept of shopping in the digital era.
But B2B companies aren’t exempt from the AI revolution either.
On the contrary, B2B operations come with their own set of challenges which the latest technology can help overcome.
It doesn’t only affect strategy and internal operations, but it’s helping refine B2B interactions and meet customer expectations in a landscape where buying decisions involve entire teams of professionals.
That being said, any B2B company, no matter the scale, should plan for implementing these technologies in order to reach digital maturity in the future.
In the following article, we’ll talk about how AI can help B2B startups gain a steady advantage and spur exponential growth.
Boosting lead generation
B2B lead generation is historically a strenuous manual process of researching potential clients, categorizing the people with purchasing influence within companies, and finding contact information.
A new-born company entirely depends on these processes to grow their database, assigning a large portion of their efforts to sourcing new leads.
In this aspect, machines don’t only help with gathering the bulk of information, but can also analyze unstructured data to determine who is a viable prospect and to pick out the decision-makers with purchasing roles who should be contacted.
Using machine learning, it can even analyze sales calls (which are virtually impossible to analyze manually) to define patterns and highlight data points which will, in turn, serve to segment targeted clients and help develop personalized messages.
Predictive sales efforts
This is already common in the B2C landscape, where customized ads and suggestions flood search results and social media feeds.
In the same manner, B2B companies can use predictive analytics to offer their customers suggestions and direct them to the range of services or products that would complement their business needs and previous purchases.
B2B companies have been striving to do this in the pre-digital world as well, but with artificial intelligence on the rise, there is much more opportunity for upselling as well as sustaining collaboration.
Needless to say, standards have risen among consumers in all landscapes, but today’s business owners are coming to expect companies to anticipate their needs.
Both marketing and sales teams can directly rely on the power of AI to analyze large quantities of data and provide insights which would help streamline lead scoring.
Machines can identify patterns among customer groups to direct teams to the right customers at the most desirable times, help prioritize sales efforts, and provide the information that sales and marketing teams need to fine-tune their strategies.
Essentially, monitoring customer behavior is going far beyond web analytics, as machines analyze data for meaning and help businesses learn more about their customers.
By being able to improve their strategy across numerous functions based on customer behavior, businesses who put this technology to use are at a significant advantage regarding customer retention.
The technology is especially changing customer service and loyalty marketing, where machines are being programmed to respond to input from customers efficiently and at all times. Not only that, but they can gather data from interactions both to provide insight to marketers and (as is the case with sophisticated chatbots) to use when responding to future inquiries.
Businesses have a much better chance to provide efficient customer service and a seamless customer experience, which is making interactions simpler – ultimately helping build long-term loyalty.
Managing the cash flow and gaining access to credit
AI is helping small B2B companies overcome one of the biggest challenges: how credit works in the B2B landscape. With late payments and cash from their customers also trapped in accounts receivables, small B2B companies are especially affected.
Adding to this is the fact that they’re usually unable to access credit through conventional channels, which rely on incomplete metrics and consumer models when making credit decisions.
Automated credit programs are already helping businesses get paid for their goods on time and avoid working capital deficits.
With the help of AI, non-traditional lenders can use data sources to gain a more wholesome picture of a small business’s health and credit viability.
The sophisticated risk models and valuable insights are allowing fin-tech lenders to provide funds for the majority of small businesses who were denied access to credit by banks.
Being AI-driven, the process is significantly faster, as lenders have at hand all the analyzed data to make swift decisions for approval.
All this points to the underlying theme of AI and machine learning: it frees up humans to strategize effectively and do all the creative work.
Many large businesses have implemented AI solutions across business operations, but now is a great time for startups to adopt the technology as it will almost automatically get them ahead of competition.
Of course, it’s an investment, and startups are rarely in a position to build their own teams that would put the technology into action. But AI capabilities can be outsourced, and this investment might be the best one yet.
What are the top uses of Artificial Intelligence for B2B?
- Boosting Lead Generation
- Predictive Sales Efforts
- Customer Loyalty
- Managing Cash Flow