After more than a year of the COVID-19 pandemic, companies have been compelled to rethink how they find and serve customers. The result is a six-year acceleration in digital transformation across the board, with 97% of executives saying that the pandemic has accelerated their digital transformation, and 95% looking for new ways to engage customers, according to a Twilio Report.
To adapt and prosper, companies will need to make sure they have the right tools and methods in place to adapt and thrive in this market.
What’s wrong with the everyday marketing strategy?
Everyday marketing segments customers based on the products they buy. This means paying more to acquire customers who have bought higher-end products in the past, or demonstrate an interest in potentially purchasing more expensive products.
There is a clear downside to this approach.
Customers who purchase the cheapest product first may quickly become recurring consumers, generating more profit in the long term. Customers who buy expensive items first maybe just one-off consumers. Mid-tier customers may also generate more revenue as they purchase items more frequently.
The issue with this approach is that the actual value of each customer remains unknown.
In answer to this, what if you could predict every customer’s lifetime value for the next ten years? This would play a key role in your marketing strategy.
Introducing Customer Acquisition Cost (CAC) and Customer Lifetime Value (CLV)
With shopping as easy as search and click, there are many business benefits such as new global audiences but also challenges such as intensified competition.
So how can you successfully market a product or service online? It comes down to CAC and LTV to determine Margin and Lifetime Profit.
By tracking Customer Acquisition Cost (CAC) and Customer Lifetime Value (CLV), you will be able to focus on generating the highest ROI out of every dollar spent on marketing. With the right tools, you’ll have access to valuable data and feedback on overall performance to reduce CAC and increase the proportion of high-value customers with an extended CLV.
First, you’ll need to link marketing inputs to bottom-line results. There are two ways to do this:
Attribution models can be used to identify a set of user actions that contribute to the desired outcome such as sign up or purchase by assigning a value to each occurrence.
Marketing Mix Modeling (MMM) assists with precise source attribution where the impact of a particular marketing input is inferred through economic analysis techniques and hold-out experiments.
Second, you’ll need to determine predictive LTV. Two distinctions are necessary for this step:
Historical CLV is the actual value generated by a customer since they first purchased from your business. It’s only possible to measure this with a long track record, and it doesn’t show full LTV.
Predictive CLV is the prediction of the future lifetime value of a customer acquired today through a particular channel.
For this reason, we use predictive CLV to measure predictive LTV. This lifetime portion of the CLV equation can be challenging to calculate. It requires user tracking on an acquisition cohort basis, where data is grouped by the date the customer first purchased rather than first purchase date.
By observing the retention curve, it’s possible to ascertain the average expected lifetime for a newly acquired customer. In addition to tracking CAC, CLV, and Gross consumer margin, each metric can be segmented into further data inputs such as:
CAC- cost per impression, click-through rates, and purchase conversion rates
CLV- average lifetime duration, retention curves, average order size, transactions per period, and margin translation, to name a few.
Take Advantage of CTV
In order to keep up with the competition, companies need to drive greater CLV through improved targeting and lifecycle marketing.
There’s a clear need to increase the effectiveness of digital marketing in a more competitive digital market.
A few companies have revolutionized this approach in terms of acquisition and retention by:
- Attracting high-value individuals by creating lookalike audiences
- Using value-based bidding methods to allocate CAC based on the long-term value of each potential consumer
- Refining messaging based on the type of content that resonates with high-value customers
- Converting only the highest value prospects by revamping targeted campaigns
- Using CVL and purchase behavior to determine which customers should receive discounts or promotions