It’s never been more important to understand your customers in a way that is useful for driving revenue for your business. All leaders need to know how to leverage customer insights and drive more revenue from returning customers, and the literature around why this is a better ROI than constantly acquiring (and losing) customers is legion. Here are a few tips on making this come to life:
An Insight into Customer Insights
While Customer insights appear to be all about understanding customers’ needs, behaviours, preferences etc, not all insights are equal. The first thing to figure out how far you’re going to get is to know the entitlement you begin with – the data you have.
Our view is that the best stuff comes from the transaction and behavioural data, and less from profiles and demographics, for a couple of reasons:
Transactions and Behaviours are good data
These come from billing or online systems, are first-party data you own, and contain enough signals to make many of the decisions you need. If your goal is to figure out who’s going to do a Repeat transaction, there’s enough in the transactions and behaviours to go by, without waiting for Profile information.
Profile data = Infinite Procrastination
For many industries, waiting for profile data can be an infinite wait. You need to put in place systems to capture it, send out profile-update surveys, get front-line staff to ask Qs and so on. This can take a very long time to give you a half-decent fill rate in your customer database, which is time lost.
Similar Profiles have vastly different behaviours
If you’re looking at predicting which of your churn base is likely to be won back, chances are there’s little commonality from a Profile perspective that will help. Gender/ Location/ Income etc don’t help much when it comes to predicting behaviour. They do help a LOT when it comes to getting the right tonality, but from a sheer utility perspective – our approach is to tap into transaction data first, and fast, before getting to profile information.
Customer Insights (that are worthwhile)
Of the many customer insights you might seek, we’ve found a few to be more immediately useful to drive business goals:
The simplest, the most insightful, and yet oft-overlooked. Lifecycle insights are simple metrics that tell you how healthy the customer base is. These help set goals and can drive the entire CRM effort. Sample metrics include:
Repeat behaviour: How many repeats, and within what time frame? What is the contribution of Repeat revenue in a month as against New revenue?
Retention Metrics: A variant of Repeat, this typically looks at how many customers that transact in a year are retained in the subsequent year.
Churn and Winback Metrics: How many customers are lost, after how long do we call them “churned”, and how many of them are won back?
Stickiness and Stars
Insights into what makes for a loyal or “sticky” customer. What they buy, how often, how quickly etc. Loyal and Star customer profiling provide a wealth of insight into the ideal customer behaviour you’re chasing.
Combining product adoption with lifecycle thinking leads to some great insights. Instead of just looking at what is the product mix being bought, one looks at what’s the mix at different stages of the lifecycle.
What’s the entry point, and also what was the entry point for those who went on to become Star customers? Which product seems to lend itself the most to repeat? How much is the category adoption amongst customers and what are the category associations? And finally, what seems to be most associated with customer churn?
These often go hand in hand – insight into what makes a Location different, as well as what is the buying pattern over time bands – days of week/ month part/ season etc.
Here again, combing Location/ Time data with the Lifecycle often gives the best insight. Knowing that there is a sub-segment among your Stars that are weekday buyers is useful to craft targeted campaigns just for them.
Campaign and Offer Responsiveness
Finally – a great piece of insight to delve into is to know what nature of nudge works to get customers to buy. Does it work better to send personalized messages? Do recommendations work? Does day and time matter? What’s the right cool-off between messages? What tonality resonates?
Putting this to use
Do better Targeted Campaigns
Better, more targeted, hyper-personalized campaigns that get better conversions and Lift. The starting point to these is knowing your customer better.
Do better Mass Campaigns
Mass Campaigns can and should be smart campaigns. Yes, you may talk to the entire base but the offer and tonality may vary by segment. Timing can be picked, the offer can be tweaked.
Set better Goals
It takes insight to set good CRM goals – what Repeat/ Retention/ Churn Prevention and Winback goals you chase come from the customer insight you have.
Improve your ROAS
The ultimate goal is ROAS – get more revenue, at a lower cost. Which means better targeting without missing opportunities.
Align the Org. for Loyalty
This doesn’t mean a Loyalty Program. This means the always-on hunger for customer insight and how to put it to use to retain customers, better. Stay customer-obsessed, by being data-driven.
Why SOLUS AI?
We’re a System of Intelligence providing a personalization & decision engine, built for Customer obsessed businesses. While at one end we operationalize Recommenders, Predictive Scores and Smart Campaigns, an equally large part of our value proposition is getting businesses closer to their customer data by giving them all the customer insight they need, on tap.
These tools include:
- Repeat customer base and revenue tracking.
- Bounce curve or Interpurchase cycle tracking.
- Repeat Cohorts.
- Glue number and Glue cohorts. (how sticky is the customer base)
- Multiple Segmentation schemes with segment profiling.
- Customer frequency distributions.
- Segment movements over month/ quarter/ year.
SOLUS AI’s Campaign Insights revolve around Incrementality measurement and encompass:
- Outreaches and channel split.
- Incremental Revenue, Lift, TG vs. CG metrics.
- CRM KPIs tracking such as Repeat, Retention, Winback etc.
- Any vs. Hard Response. (bought the specific product)
- Conversion Analysis – what was bought in the conversions.
- Attribution views – Last Touch vs. MTA
- Yield reports that specify the ROI from campaigns.
In conclusion, if you’re looking to enhance your user experience and maximize the potential of your business, look no further than our machine learning-based recommendation system. With cutting-edge technology and expertise in artificial intelligence, we have revolutionized the way businesses connect with their customers. Contact us for intelligent campaign & customer insights.