But there are measurements and tools customer marketers can deploy to help (as long as they’re backed by unified and accessible real-time data).
One of the most useful metrics in a customer marketer’s armoury to win the battle for customer loyalty is frequency, which measures the number of interactions a single customer has with your brand over a given period of time. It’s a crucial KPI for tracking, projecting and advancing a business’s financial and brand health.
Want to dive deeper into this topic? Check our on-demand webinar, Strategies to Drive Shopping Frequency and Revenue Growth.
That being said, it’s become more difficult in recent years to measure and encourage customer loyalty. However, by leveraging first-party data and the power of artificial intelligence (AI), businesses can unlock new opportunities to drive customer loyalty and boost purchase frequency.
Over the next few weeks, we will delve into the importance of measuring and increasing purchase frequency, explore the obstacles to doing so, and provide practical advice on leveraging first-party data, predictive analytics and AI to overcome these challenges.
The Significance of Purchase Frequency
Purchase frequency refers to the number of times a customer makes a purchase from a specific business within a given time frame. To calculate it, you’ll need to divide your total number of orders by the number of unique customers within that time frame.
Frequency is a key metric for businesses aiming to drive revenue growth and build long-term customer relationships. Here’s why:
- Revenue Generation: Increasing purchase frequency directly translates into higher revenue. By encouraging customers to buy more frequently, businesses can enjoy a steady stream of income and reduce their reliance on customer acquisition (which, as we know, is 5-7x more expensive than retaining customers).
- Customer Retention: By building strong relationships with existing customers, businesses can boost customer retention rates, increase lifetime value, and reduce customer churn.
- Customer Satisfaction: Satisfied customers who purchase frequently are more inclined to spread positive word-of-mouth recommendations. Their enthusiasm can drive new customer acquisition, amplifying the effects of a well-executed marketing strategy.
- Customer Loyalty: Of course, this all has a knock-on effect for brand loyalty – customers who purchase more frequently are more likely to develop a strong bond with your brand.
That all sounds great, right? But tracking and encouraging purchase frequency is actually more complicated than it may appear on its face.
The Challenges of Measuring Frequency
There are many factors that can contribute to inaccurate or incomplete frequency measurements:
- Fragmented Customer Journeys: Customers interact with businesses through multiple channels, both online and offline. Tracking their purchases across various touchpoints and consolidating the data to determine purchase frequency can be complex, especially when customers switch between different platforms.
- Lack of Unified Data: Many businesses struggle with fragmented or siloed data systems. When customer purchase data is scattered across different databases or platforms, it becomes difficult to consolidate and analyse the information effectively.
- Incomplete Customer Profiles: To track purchase frequency effectively, businesses need comprehensive customer profiles that include past purchase history, preferences, and behavioural data. However, incomplete or outdated customer information can hinder accurate tracking and analysis, leading to inaccuracies in measuring purchase frequency.
- Privacy Features: Privacy features like Apple’s Hide My Email, which allows users to generate unique, random email addresses for sign-ups and online interactions, can make customer identification more challenging. (We’ll discuss this in more detail in an upcoming post!)
- Limited Data Accessibility: In some cases, businesses may not have access to comprehensive customer data. If customers make purchases through third-party marketplaces or retailers, the business may have limited visibility into those transactions, making it challenging to track purchase frequency accurately.
- Time Lag in Data Updates: Real-time data updates are crucial for accurate tracking of purchase frequency. However, delays in data synchronization and reporting can result in outdated information, making it difficult to measure purchase frequency in real time.
- Cross-Device Tracking: In today’s multi-device environment, customers often switch between smartphones, tablets, and desktop computers during their purchase journey. Tracking purchases across different devices and attributing them to the same customer accurately can be a challenge, impacting the accuracy of purchase frequency measurements.
- Seasonal or Cyclical Purchasing Patterns: Some businesses experience significant fluctuations in purchase frequency due to seasonal or cyclical trends. Tracking and analysing purchase frequency accurately requires accounting for these variations and adjusting strategies accordingly.
Though it comes with its challenges, accurately measuring and increasing purchase frequency is a worthwhile endeavour.