Difference Between B2C and B2B SaaS

In this article, we understand the difference in B2B vs B2C Space

Company (Business to Business)
* As the name suggests, B2B Companies build products for business. Famous examples are Salesforce, Slack, Freshworks, Zoho.

B2C company (Business to Customer)
* B2C companies build products for customers. Famous examples are Uber, Swiggy, Amazon, Flipkart.

Consider the example, Classification problem of the incoming email is important or not. In B2C space, user behaviour will be same and more likely one model is enough. When serving for B2B Space, each business will have their definition. Worst case, we have to build a separate model for each business. What works for one business many do not perform as same as other business. It will require separate model monitoring for different customers.

Thus, building ML features in B2B space vs B2C space can be analogous to “Planning for Love Marriage” to “Planning to arrange marriage”. Building ML features takes too long a cycle, more complex and thus requires more convincing to become successful.

I took the below four problems as reference to explain the B2B Case study

Canned Response Suggester (CRS)
“Canned Responses” are predetermined responses to common questions that allow you to insert pre-formatted content into your message

Impact: All the sales, presales, customer support will have to reply to almost the same set of queries. Predicting the correct set of canned responses can reduce the workload of typing redundant mails.

Field Classification in Customer Support (FC)
* Given a customer support ticket, the required fields such as Category, Priority, AssIgnment group have to be filled by classification model.
Impact: Every day, 1000 of tickets come to the customer support team. We can classify it before sending it to the required person. Filling these fields actually requires the workload of the L1 or first level support.

Customer Churn Prediction (CCP):
* In the Business, customer churn happens when existing customers or subscribers stop doing business with a company or service
Impact: it is easier to keep the existing customer than to get new customers. Thus, information about which customer will probably churn earlier will be very useful.

Sentiment Analysis in Social Media Brand Reputation (SA):
* Sentiment Analysis classifies the text as positive, negative, or neutral
Impact: This sentiment information will be helpful. Negative customer issues can be addressed and we can increase sales from positive customers.

Now the case study are well defined. In the next article, data exploration specific to this case studies will be studied. Please click here for next article.

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