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Unlocking Insights with Payment Analytics: A Guide for MSPs on Leveraging Payment Software Analytics

According to a Recurly study, only 7% of respondents report confidence in their organization’s analytics, technological, and operational capacity

Furthermore, 100% of respondents report feeling the impact of failed payments in their organizations

This lack of confidence demonstrates a substantial chasm in an MSP’s effectiveness and ability to leverage payment data for financial decision-making.

This is why payment analytics tools—and a strategy for using them to drive value—are becoming indispensable for MSPs.

Payment analytics is a data-driven approach that analyzes payment data to deliver actionable insights about payment activities, trends, and risks. 

It involves collecting large amounts of payment-related data, analyzing it with algorithms or payment automation software data, reporting insights, and forecasting trends to inform business decisions.

Doing so creates several positive outcomes for MSPs:

  • Enhanced cash flow
  • Improved client retention
  • Better operational efficiency
  • Financial stability

This article examines how payment analytics achieves these outcomes and why it’s the key to transforming MSP financial management.

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What is Payment Analytics?

At its core, payment analytics uses data analyses in payment processing to better understand how payments are handled. Consequently, you can leverage data analytics techniques to improve payment performance. 

Reviewing your bank account balances or looking at your profit and loss statement pales in comparison to payment analytics.

When used to its maximum potential, payment analytics drills down into the behavioral data accounting for every transaction so you can understand your financial performance's why and how.

Payment analytics encompasses three critical functions:

  1. Data Collection
  2. Data Processing
  3. Insights

Let’s look at each of these in a bit more detail.

1. Data Collection

Payment analytics relies on the data collected to provide the most helpful insights for MPSs.

The various payment data points collected include: 

  • Transaction Information
  • Payment method
  • Client information
  • Merchant information
  • Processing information

Let’s review each one of these in detail.

a. Transaction Information

Transaction data captures the core details of every payment in or out of an account, including: 

  • Precise time and date of the transaction
  • Amount paid
  • Currency used
  • The geographic location in which the transaction occurred 

Payment analytics will also use transaction information to track trends and deviations over time.

For example, it could detect an uptick in refunds or chargebacks from a particular client or service, which could point to a recurring issue with that service or product. 

With this knowledge, MSPs can take action before their cash flow is impacted. 

With early warning, the MSP could take remedial action—such as reviewing the service quality or contacting the client to resolve issues—to prevent more refunds.

b. Payment Method

The payment data also contains transaction processing details, including: 

If an MSP notes an uptick in its clients' use of flexible financing (B2B buy-now-pay-later ), it might emphasize those payment forms to improve the customer journey. 

Awareness of these preferences allows MSPs to curate their payment options and incentivize clients to utilize faster or simpler payment methods.

c. Client Information

Client information includes names and contact data, payment histories, trends, and preferences. 

With this knowledge, MSPs can create a rich client profile to help forge better client relationships and maximize available resources. 

For example, if a particular client is prone to late payments, an MSP can set up an early warning system to send reminders or offer flexible payment terms to encourage timely payments.

On the other hand, clients who have paid on time might also be offered some sort of discount or loyalty rewards to motivate them to remain longer as clients.

d. Merchant Information

Merchant information includes the merchant ID, business type, and the transaction's location.

With this context, providers can fine-tune their service offerings to focus more on lucrative industries or develop specialized products for different business categories.

For example, an MSP providing services to hundreds of clients might analyze which different categories of businesses (or industry niches) generate the most revenue or the least payment friction. 

e. Processing Information

Processing information is also valuable for assessing the efficiency and effectiveness of the payment process. 

This includes details about:

  • The payment gateway
  • The payment processor handling the transaction
  • Transaction metadata

This data could uncover insights such as transactions taking too long at the authorization stage or a non-negligible percentage of transactions accumulating a disproportionate share of transaction fees.

Then, an MSP can take proactive steps to alleviate the problem. 

For example, suppose several transactions are always delayed at the processing stage. 

In that case, the MSP can switch to a different payment gateway or negotiate improved terms with its existing payment processor to ensure its operation is as smooth and cost-effective as possible.

2. Data Processing

Algorithms that seek patterns, anomalies, and trends in scrubbed and processed data help MSPs turn raw payment data into actionable insights.

AI and machine learning algorithms are particularly helpful in this regard, as they can handle large data sets and spot intricate patterns that traditional analysis might fail to catch.

For instance, MSPs can use AI to identify small changes in payment patterns that signal a client may be under financial strain and can act sooner to address a potential payment issue. 

Machine learning models become more accurate over time by learning from new data and more effectively predicting future payment patterns.

3. Insights

The insights gleaned from payment data analysis can inform smart business decisions that improve your profitability. 

This might mean changing payment terms, sending reminders earlier, or making payment more convenient for the client.

Moreover, insights could reveal one service offering is much more profitable than others. 

This helps you refine marketing strategies, deploy resources more effectively, or even adjust prices to capture the full demand for the services clients want most.

How to Harness Payment Analytics for MSP Operations: 11 Ideas & Strategies

Having established the power of data collection, processing, and insights, we will now move on to how MSPs can harness it.

Payment analytics means more than simply tracking payments for an MSP. It also aids in payment optimization, client retention, and operational efficiency.

1. Multi-Factor Authentication (MFA): Strengthening Security Measures

A 2021 Juniper Research report estimates the global cost of online payment fraud will reach US $206 billion by 2025.

Another Juniper Research report from 2022 predicts businesses will lose more than US $343 billion to online payment fraud globally by 2027. 

With the increasing level of payment fraud, MSPs must be extra cautious in protecting their payment systems. 

With multi-factor authentication (MFA), users must validate their identity using several authentication factors before accessing payment-related systems.

For example, users might need to enter a password and confirm their identity with a code sent to their smartphone or a fingerprint scan. 

This layered approach dramatically reduces the risk of unauthorized access, even if one authentication factor is compromised.

Payment analytics can play an important role in supporting MFA by recognizing abnormal behavior associated with logins. 

For instance, it could detect a login attempt in which payment data is accessed from an identified location but from an unknown device. 

The marriage of payments analytics and MFA helps MSPs safeguard their confidential financial data, mitigating payment fraud risks.

However, most small and medium enterprises have yet to adopt this practice. 

A 2024 JumpCloud survey of over 47,000 businesses found that in companies with 26 to 100 employees, only 34% use MFA. In businesses with up to 25 workers, the adoption rate is just 27%.

MFA, including passwordless authentication, is widely underutilized, considering a reported 81% of cyber breaches are due to weak, stolen, or reused passwords.

Eliminating the use of passwords and utilizing MFA blocks 99.9% of fraudulent attacks, making it an obvious choice for MSPs striving to boost security measures.

2. Streamlining Revenue: Identifying Consistent Revenue Streams

Identifying revenue volatility from client to client is crucial for MSPs who serve multiple clients on different schedules. 

With payment analytics, MSPs identify revenue streams with a string of on-time payments and less predictable ones to adjust their cash flow planning appropriately.

For example, payment analytics can tell the MSP that a particular client always pays on time and in full while another habitually pays late. The MSP can then offer dependable client discounts upfront for early payments or a subscription upgrade. 

Clients who habitually pay late can be offered more flexible payment terms or targeted reminders to settle their accounts.

With payment analytics, an MSP could create a better system to match revenue fluctuations, thus ensuring the predictability necessary for long-term financial stability.

3. Operational Efficiency: Automating Billing and Payment Processes

Many MSPs with large client bases still rely on manual billing and payment processing, which becomes more expensive with every client added to the list. In turn, scaling becomes difficult, if not impossible.

From when each invoice must be generated to making sure it’s paid to chasing down past-due accounts, processing payments places a considerable burden on time and resources. 

Payment analytics can spot these inefficiencies and provide a plan for automating them.

For instance, if payment history data shows late payments are a common issue, the MSP can use automation to send reminders to clients just before payment deadlines.

FlexPoint AutoPay

It can also be programmed to automatically send invoices at set intervals, reducing the chances of missed deadlines and human error.

With automation reducing workload, an MSP can dedicate its human resources to strategic, profit-growing initiatives rather than menial, error-prone tasks. 

This move from manual to automated invoicing saves MSPs time and money. 

Let’s use Circuit Saviors, a California-based MSP, as an example. 

Switching to payment automation with FlexPoint’s AutoPay feature saved them 16 hours of monthly payment admin work. It also boosted payment efficiency by 30% and increased cash flow by 30%

These results aren’t unique to Circuit Saviors, either. 

Research from Ardent Partners shows that switching to automated processes shortens the average time to process a single invoice by 81%.

Similarly, a report from the Institute of Finance & Management (IOFM) shows that the average cost for processing a manual invoice is $16. For an automated invoice, this cost is only $3.

4. Client Retention: Tailoring Engagement Strategies Based on Payment Behavior

Client retention is the lifeblood of an MSP business, and the insights payment analytics provide into client behavior can significantly improve retention efforts. 

Payment data can segment the client base according to payment habits. Often, this is those who always pay on time versus those who are frequently late with payment deadlines.

Then, you can tailor your tactics to different client segments. 

For example, you might offer loyal, prompt-paying clients discounts or reward points to sustain the relationship. 

Not only can this improve client satisfaction, but it also benefits your payment cycle.

According to PayStand data, companies that offer early payment discounts see a 15% reduction in their average days payable outstanding (DPO).

5. Risk Mitigation: Managing Late Payments

MSP Insights reports that 81% of managed services providers aren’t paid on time.

Considering the prevalence of late payments in the industry, speeding up the payment cycle and reducing late payments is important to most MSPS. 

Late payments wreak havoc on cash flow and even long-range financial planning. 

Payment analytics can give MSPs an early warning system for late payments, giving them ample time to handle any clients who may be late this month.

Who are your most at-risk clients regarding payments, and how does that information inform how you manage their standing spending? 

MSPs can answer these questions by analyzing payment data from previous years. 

Analytics show which clients are most at risk of late payments, and then MSPS can work to change that trajectory. 

Furthermore, payment analytics can also automate reminders and follow-up communications for late payments or outstanding invoices. This helps manage the time and effort needed to deal with late payments. 

6. Resource Allocation: Prioritizing High-Value Clients

MSPs quickly realize that not all clients are equally lucrative. If payment analytics is done right, it will show MSPs which clients generate the most revenue for their business.

For example, you can identify underperforming clients whose revenue doesn’t correspond to the resources they demand. 

In such cases, you can renegotiate contracts or change the service mix to ensure every client relationship is profitable.

7. Customized Billing Solutions: Tailoring Payment Options

Payment analytics also helps you create transparent and customized billing models that match exactly what clients need and how they want to pay. 

For example, some clients may prefer a monthly subscription because they always want to know precisely what they will pay. 

Others may prefer usage-based billing and consequently only pay for what is consumed.

MSPs can use client payment logs and history to determine when invoices are due based on their clients’ schedules. 

Creating a payment system compatible with a client's financial comfort can improve client satisfaction and reduce payment disputes and late payments.

Custom billing solutions can empower MSPs to stand apart from competitors by allowing for more flexible and friendly payment models for clients. 

In turn, this increases the likelihood of acquiring and keeping more clients.

Efforts to improve client retention are worthwhile — a 5% increase in client retention can increase profit by 25%

8. Cash Flow Management: Ensuring Liquidity

Cash flow is complex for MSPs, but it’s also critical. Without it, MSPs won’t be able to cover operational expenses, make the investments needed to scale the business or maintain their financial stability. 

Deteriorating cash flow can result in late payments to vendors, reduced ability to refine or upgrade technology or services, and a general degradation of service quality. 

Ultimately, inadequate cash flow risks driving away clients, making it difficult or impossible to scale and ultimately failing as a business. 

In fact, according to data from the U.S. Chamber of Commerce, 82% of small businesses fail due to inadequate cash flow

Effective cash flow management ensures MSPs always have the liquidity they need to pay their bills, reinvest in the business, and sustain long-term growth.

Recurring payment models can help, but proper management of payment analytics can help them track when they’ll receive payments and which clients will most likely delay payment.

For instance, you may use payment analytics to predict when most of your clients will pay so you can budget expenses and investments in advance. 

With this information, you will know when you are more likely to run out of cash during a given month. You can anticipate whether it has sufficient liquidity to keep the business running if one or two invoices get paid late.

Payment analytics also determine the best time to send out invoices and reminders. This helps you manage cash flow and reduce the time it takes to convert invoices into cash.

9. Accounts Receivables Recovery: Optimizing Collection Strategies

Chasing overdue payments is time-consuming, but payment analytics can help strengthen MSPs’ debt recovery by revealing patterns in client payment behavior.

For example, analytics could tell you that one client segment often responds best to an intensive round of early payment reminders. In contrast, one-to-one interaction with their account manager best serves another client segment.

Ultimately, MSPs can tailor best practices for collecting outstanding payments without hurting client relationships

Payment analytics can also identify potentially high-risk clients before they become an issue. With this advanced notice, you have time to renegotiate payment terms or insist on payment to minimize the risk of default.

In some cases, accounts receivable processes can even be automated. 

Progressive reminders can be sent based on payment analytics. When deadlines approach, late fees can also be automatically applied to outstanding balances.

10. Pricing Strategy Optimization: Maximizing Profitability

Utilizing payment analytics is a competitive advantage when an MSP determines its pricing strategy. 

Services can be underpriced or undervalued, but payment analytics pinpoints the most profitable services by analyzing clients’ payment behavior. 

For example, suppose you learn your clients are willing to pay more for premium services. These services might be better security or faster response times. 

In that case, you can adjust pricing tiers that include those services to reflect that demand. 

Conversely, if particular service bundles consistently underperform, you might offer discounts or other promotions to attract more clients.

Payment analytics also helps you manage pricing relative to client fiscal health. 

Discounts for early payments and progressive payment plans for those in financial distress can improve cash flow while maintaining profitability.

As explained above, early payment discounts can drastically shorten the payment cycle.

However, their benefits extend beyond time savings. According to data from Kyriba, offering dynamic discounting can reduce costs by 8 to 12%

11. Enhanced Reporting: Providing Clear Financial Insights

Payment analytics provide MSPs with easy-to-understand reporting created from consolidated data.

This data identifies and summarizes key performance indicators (KPIs) such as: 

  • Cash flow
  • Revenue per client
  • Growth projections
  • Risk exposure

These KPIs inform decisions about reallocating resources, supporting new service opportunities, and promoting better client relationships.

This gives stakeholders greater visibility into their MSP's finances and their trust and confidence in the MSP. It creates a shared understanding of the company’s current financial performance and long-term strategy.

Conclusion: Empowering MSPs Through Advanced Analytics

This article has discussed different scenarios for how payment analytics can help MSPs achieve new heights in their financial management. 

We have also explored the intricacies of payment data collection and processing and the resulting insights for the MSP. 

From identifying consistent revenue streams to automating billing processes and enhancing client retention, payment analytics' power lies in its ability to transform raw data into actionable strategies that help MSPs grow.

Whether automating their billing, preventing late payments, or enhancing client communications, FlexPoint has the tools to help MSPs get paid faster, smarter, and more predictably.

FlexPoint MSP Payment Automation Platform

When Compunet Technologies, a California-based MSP, needed a new payment solution after complications from its previous provider's acquisition, the managed IT solutions provider turned to FlexPoint

With FlexPoint, Compunet can now see a holistic picture of its payment data. It receives notifications about every aspect of billing and payments, including past-due balances.

With this enhanced billing visibility, Compunet shortened its monthly billing time from five hours to just 15 minutes. With a four-fold increase, billing cycles also sped up dramatically.

Your MSP can achieve improvements like this, too. Transform your MSP's financial management with FlexPoint's cutting-edge payment analytics solutions

Discover how our advanced tools can provide the insights needed to make more informed decisions and enhance operational efficiency.

Visit our website or contact us today to learn more and get started.

Additional FAQs: Leveraging Payment Analytics

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Table of Contents
How Can MSPs Start Integrating Payment Analytics Into Their Existing Systems?

MSPs should begin with payment analytics tools with easy-to-adopt APIs that can be scaled as their business grows. 

Moreover, their team needs to be trained to interpret the data and respond to the insights generated by the tool. 

The above article shares several strategies for responding to the insights garnered from payment analytics.

Can Payment Analytics Help in Reducing Fraud and Improving Security for MSPs?

Yes, payment analytics allows MSPs to identify patterns of abnormalities in payment data and respond quickly to fraud attempts. 

Payment analytics enhances security levels when combined with other robust security methods, such as multi-factor authentication.

What Future Trends in Payment Analytics Should MSPs Be Aware of to Stay Competitive?

Begin with predictive analytics powered by artificial intelligence (AI), blockchain for secure and transparent online payments across institutional boundaries, and cutting-edge real-time data visualization. 

Dedicated learning and information about these and other developments will further enhance MSPs’ ability to compete and strengthen their bottom line.