Quantitative analysis of renewal rates If it cannot be quantified, it cannot be measured. We need to find some predictive indicators that can measure whether customers will executive list renew their contracts, and then analyze the health of these indicators in detail. The search for indicators is explained in detail in the actual combat note 2. To sum up, for TOB's products, I think executive list that only when the customer gets the value of the product can the customer renew the fee, because in essence, I think that TOB's purchase of SaaS software is an investment behavior, and it needs to see returns.
The obvious return in business (efficiency improvement/direct output) is unlikely to continue to invest; this is different from TOC, TOC executive list may be a consumption behavior, and the main appeal of consumption is experience. Therefore, how to find and measure whether the customer gets and how much product value is obtained is critical. It is executive list recommended that you refer to the following criteria when doing quantitative analysis of renewal rates: First of all, we need to clean the data and exclude non-target customers, because it is not excluded that sales will sign a small number of non-target customers.
Do I have product value metrics, such as product usage activity, health score; Whether these indicators really feedback the core value of the product, if not, how to adjust it; Whether these indicators and the renewal rate have reached a statistical executive list correlation (attribution, correlation analysis), I have improved these indicators, whether the renewal rate is executive list certain or has a high probability of increasing; Whether these indicators are significantly different in different customer tiers, contract stages, customer stages, customer sources, and maintenance groups.