How predictive analytics and automation can help you transform collections
Updated: Sep 16, 2022
B2B companies often find it challenging to collect payments from customers who have fallen behind on their bills. Unlike B2C companies, which can reach out to their current and past customers via email, text, phone, and in-person conversations, B2B companies must rely on traditional methods of debt collection, such as legal action and credit reporting. Traditional methods of debt collection are expensive, time-consuming, and ineffective for customers who are unable to pay. Instead of using these methods, B2B companies are increasingly turning to modern technologies that make it easier to reach customers who are behind on their bills.
What are the Downfalls?
B2B SAAS businesses scale a customer by adding more products to sell to the same customers or self-contained systems that are added opportunistically over time and the acquisitions of new companies with products. But as the businesses grow, the Quote to Cash [Q2C] process grows in complexity and becomes fragmented because of growth in products, channels, and platforms. In these situations, the ERP and CRM platforms are in catch-up mode to the core applications, which are the essential revenue drivers. B2B SAAS Organizations lose significant money in fragmented Q2C processes, leading to:
Lack of customer revenue visibility, churn and upsell opportunity
Increased challenges in billing, invoicing & collections
A poor understanding of customer revenue,
Lost upsell & cross-sell opportunities,
Failure to collect money on time,
And gaps in cash applications.
Over time, these challenges need untangling with a data-driven approach. Organizations can fix the processes by implementing and installing a new system which will force it to go through a complete & thorough review of the processes, and redesign. But this approach is expensive, may not always be easy to implement, and can take a long time. A faster and quicker process fixing can be achieved by taking an analytical data-driven view of the key segments, outcome segments. This approach is more result-driven and can help uncover process bottlenecks, and challenges much faster, fixing them early in the life cycle.
What Makes It different?
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Bottom-up decision tree view of segments
Building Contract & Order Visibility
Q2C visibility processes start with understanding two separate threads one of which begins in the salesforce or the front-end CRM and the other in billing & accounting software. It is important to begin the journey at both ends for a quick understanding of the different lenses.
It is important to extract the customer information, understand key customer id, contract information, and build trackable order data from the contracts. This is a complex and complicated process. Most organizations have a mix of order types which may include measuring multiple delivery and action variables.
For ad-hoc purposes:
The organization needs to build this database, generate a taxonomy or method of segregating the contract types, and way to measure their contract obligations. Before implementing any large-scale contract lifecycle management program, it is easier to find if there are other recordings of contract types, orders, and what needs to be billed. It is important to build the revenue leakage data mart, understand the potential billing events and reconstruct if the organization is billing correctly all the billing events. It is often a difficult and painstaking exercise and AI tools like NLP, RNN is useful in extracting document information and structuring them.
A well-managed contract billing can help reduce disputes in debt collections. Writing and managing complex customer contracts can help organizations streamline collections by improving customer satisfaction, generating timely invoices, and improving visibility. Each agreement specifies the billing terms, contacts, and limits, thereby significantly reducing the chances of disputes. An automated contract billing management system can help organizations solve these problems by:
Automating business processes,
Easing complex billing scenarios,
Supporting business management in understanding
And analyzing billing events and increasing reporting accuracy.
Also, there are multiple people and at times multiple departments in a company responsible for B2B purchasing, which makes B2B billing a long and tedious process. It is often a lengthy process of reviewing and approving the invoices before releasing the payment as the individual's supporting payments are usually not the ones who initiate them. The billing contracts need to be clear, and the ability to write and manage contracts is essential for proper AR management.
Product usage analysis:
It refers to monitoring how the customers are interacting with the product, the frequency of usage, and why they are doing what they are doing. Not only does it help improve user experience by helping track the product data, but it also indicates products might need more attention during debt collection. The products that are used frequently would be required again by the customer, and the collection would be easier, but the products that are not being used frequently might be identified as high-risk products, as the customer might discontinue purchasing, which may result in delayed payments.
As organizations grow, the growth in the number of customers making payments with multiple payment channels grows. Different customers prefer different payment methods ranging from cash, checks, cards, wire transfers to payment gateways. To keep a proper track of the payments received, data influx from multiple sources needs to be visualized, lack of which leads to the payment visualization and understanding going down. An increase in the number of products also accounts for growing billing complexity, with each product impacting the billing procedure. One customer might pay for one product but delay the payment for another product for a long time, which affects the payment cycles. Such long billing and payment cycles make the billing systems even more challenging. Managing the AR invoices enhances cash flow and helps debt collection by reducing non-payments. Maintaining a system for sending out invoices is essential for reducing the AR risk. An automated system that notifies the customers before sending an invoice keeps track of the payments, sends late invoice notices, transfers the overdue invoices to the collection team can help ease the collection process. It also provides the organization with the ability to present their customers with precise, well-managed AI-enabled invoice matching that offers better visibility, builds trust, and speeds up the collection process.
Tracking Delays and DSOs
1. Analytics Keep You a Step Ahead:
The very first requirement of an effectively managed collections system is proper and timely billing. The invoices generated must be accurate, complete, provide all the required information, must be processed, and sent timely and to the right person to avoid payments from being deferred or neglected. Automated billing, accurate visualization and tracking, proper visibility to the client, timely follow-ups, and the use of data to analyze and predict bad debts can lead to faster collections and improved cash flow.
2. Improving the visibility of the process
Understanding payment processes to track and review payments can:
Improve collection and eliminate disputes.
It can help track delayed payments and identify if it gets regular with a specific customer.
Help avoid false rejections by identifying trends
Reduce fraudulent transactions by training a detection model.
Provides real-time insights that help make critical business decisions,
Offers end-to-end information on the expenses made on payment processing,
Provides a complete view of the model, route, provider, and currency of the payment made.
3. Predictive analytics
Predictive analytics can help reduce overwhelming debt considerably:
Before collections, by providing an analysis of prior payments;
During collections, for prioritizing customers and customizing settlements;
After collections monitor the products that need attention.
Identify high-risk accounts and forecast the effective treatment and payment methods for each account. It takes a combination of digitization, analytics, and technology to run a B2B collection process smoothly. Multiple systems that automate the contract billing, invoicing, usage monitoring, invoice matching, AR tracking. It can be integrated with various systems for a clear view of the received and the pending payments and to help manage the debt.
There is a long way for analytics and AI solutions like chatbots and virtual assistants to transform the way collections are managed and cash flows are improved. Nevertheless, the exponential growth of A.I and Analytics in transforming every industry has surely made us say “Future is Now” So, are you ready to leverage the power of A.I and Analytics to take your business to the next level? Leveraging the power of analytics and AI for debt collection, Get in touch with the industry experts! Reach out to us at www.softsensor.ai or email@example.com