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How can you forecast customer retention changes more effectively?

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Customer retention is a key metric for any business, as it measures how loyal and satisfied your customers are with your products or services. However, forecasting customer retention changes can be challenging, as it depends on many factors, such as market trends, customer behavior, product quality, pricing, and competition. In this article, you will learn some tips and techniques to forecast customer retention changes more effectively, and how to use them to improve your budgeting and forecasting process.

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Vivek S.

CFO/ GCCs/ Shared Services /Global Operations Leader

1 Understand your retention drivers

The first step to forecast customer retention changes is to understand what drives your customers to stay or leave your business. You can use various methods to identify your retention drivers, such as customer surveys, feedback, reviews, loyalty programs, referrals, and churn analysis. By analyzing these data sources, you can find out what your customers value, what their pain points are, what their expectations are, and how satisfied they are with your offerings. You can also segment your customers based on their retention drivers, such as demographics, behavior, preferences, and needs.

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Ankit Saraya, CA

Finance Controller | Strategy | Corporate Tax | FP&A | Mergers & Acquisitions | Consolidation | Finance Transformation | Financial Reporting | Regulatory Compliance | IFRS | Fintech | Ex-RIL | CA | UAE Golden Visa Holder
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Effectively forecast customer retention changes by analyzing historical data, identifying patterns, and using metrics like customer churn rate. Implement customer feedback mechanisms to understand their satisfaction levels. Consider external factors such as market trends and competition. Leverage predictive analytics to model different scenarios. Regularly update your forecasts based on new data and trends, enabling a proactive approach to customer retention strategies.

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2 Use historical data and trends

The second step to forecast customer retention changes is to use historical data and trends to establish a baseline and a projection. You can use various metrics to measure your customer retention, such as retention rate, churn rate, customer lifetime value, repeat purchase rate, and net promoter score. You can also use cohort analysis to compare different groups of customers over time, and see how their retention patterns vary. By using historical data and trends, you can identify patterns, seasonality, fluctuations, and anomalies in your customer retention, and use them to adjust your forecast accordingly.

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Victor Baciu

Managing Partner @ Deodata | Helping FP&A Pros Generate Better Insights??| Finance Platform Expert
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One of the best ways to understand retention is by bucketing your customers into different cohorts. I.E All of your customers in Jan 2023 are in their own cohort, and so on. This lets you track behavior across individual groups to better understand retention over time, and can let you get insights that you'd otherwise miss if looking at aggregate data. What if certain promotions your marketing team ran lead to higher sign-ups, but all of those customers churn more quickly? By using cohorts you'll be able to understand your customer base better than ever.

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3 Apply predictive models and scenarios

The third step to forecast customer retention changes is to apply predictive models and scenarios to estimate the future behavior and outcomes of your customers. You can use various tools and techniques to build predictive models, such as regression analysis, machine learning, artificial neural networks, and decision trees. You can also use scenarios to test different assumptions and hypotheses, such as changes in pricing, product features, marketing campaigns, customer service, and competition. By applying predictive models and scenarios, you can quantify the impact of different factors and events on your customer retention, and use them to optimize your strategies and actions.

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4 Monitor and update your forecast

The fourth step to forecast customer retention changes is to monitor and update your forecast regularly, based on the actual performance and feedback of your customers. You can use various methods to monitor and update your forecast, such as dashboards, reports, alerts, and feedback loops. You can also use key performance indicators (KPIs) to track and measure your customer retention goals and progress, and compare them with your forecast. By monitoring and updating your forecast, you can validate your assumptions and predictions, identify gaps and opportunities, and make timely and informed decisions.

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Victor Baciu

Managing Partner @ Deodata | Helping FP&A Pros Generate Better Insights??| Finance Platform Expert
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A forecast isn't a one-time activity, it should be ongoing and evolve throughout the course of the year. Being able to monitor actuals Vs forecasted performance is the only real way to know if your predictions were any good. Once this becomes more regular, you'll naturally become closer to the context behind those changes.

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5 Communicate and align your forecast

The fifth step to forecast customer retention changes is to communicate and align your forecast with your stakeholders, such as your team, management, investors, and partners. You can use various methods to communicate and align your forecast, such as presentations, meetings, emails, and collaboration tools. You can also use visualizations, narratives, and stories to explain your forecast, and how it relates to your business objectives, strategies, and plans. By communicating and aligning your forecast, you can ensure that everyone is on the same page, and that your forecast is realistic, reliable, and actionable.

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6 Learn and improve your forecast

The sixth step to forecast customer retention changes is to learn and improve your forecast, based on the results and feedback of your actions and strategies. You can use various methods to learn and improve your forecast, such as experiments, tests, evaluations, and reviews. You can also use feedback, suggestions, and best practices to improve your data quality, methods, tools, and techniques. By learning and improving your forecast, you can enhance your accuracy, reliability, and relevance, and adapt to the changing needs and preferences of your customers.

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7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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Vivek S.

CFO/ GCCs/ Shared Services /Global Operations Leader
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One more very effective way of forecasting the customer retention changes in addition to all the points mentioned earlier in the article is to also observe organizational changes in customer organizations for example any changes in top management or leadership team, how these new leaders past pattern and behavior/ treatment towards your organization, how well is the customer organization doing, if their recent performance is not so great then they might be looking for bringing changes and can pose some challenges or opportunities in retaining.

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How can you forecast customer retention changes more effectively?

1

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4

5

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1 Understand your retention drivers

2 Use historical data and trends

3 Apply predictive models and scenarios

4 Monitor and update your forecast

5 Communicate and align your forecast

6 Learn and improve your forecast

7 Here’s what else to consider

Budgeting & Forecasting

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How can you forecast customer retention changes more effectively?

1

2

3

4

5

6

7

1 Understand your retention drivers

2 Use historical data and trends

3 Apply predictive models and scenarios

4 Monitor and update your forecast

5 Communicate and align your forecast

6 Learn and improve your forecast

7 Here’s what else to consider

Budgeting & Forecasting

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