5 omnichannel metrics every customer-first brand measures
Fragmented data creates fragmented customer experiences. As you work to offer the most consistent and satisfying experience for any customer journey, it’s important to collect, aggregate, and analyse data from each channel. Here are the top 5 metrics you should be tracking for a holistic understanding of your customers and your omnichannel performance.
Omnichannel is in, and it’s here to stay.
The omnichannel movement has been building steadily over the past decade. Recently, the COVID-19 pandemic pushed it into critical focus, with brick-and-mortar shops suddenly closed and a wave of consumers flooding ecommerce channels for their shopping needs.
Even in these highly unpredictable and unprecedented circumstances—where consumer behavior, attitudes, priorities, and preferences have seen and will continue to see major shifts—omnichannel businesses are staying afloat by doubling down on ecommerce to offset the lack of in-store sales.
You can’t master omnichannel retail until you learn how to measure it. Only by unifying your data and analyzing how every channel is working alongside and in tandem with each other can you begin to genuinely understand and engage your customers with the experiences they deserve.
Here are some of the most important omnichannel metrics to measure in order to understand the unity and quality of your omnichannel performance.
5 omnichannel metrics every customer-first retail brand should measure to understand performance
1. Customer lifetime value
Lifetime value (LTV) is the measure of a customer’s actual or likely value to your business over their lifespan as a customer. Typically, we think of LTV as a loyalty metric, so the greater the LTV, the greater the loyalty of your customer base to your brand. There are three approaches you can take to calculate LTV:
- Total spend-to-date: Subtract the total value of all a customer’s refund from the total value of their orders. This strategy is the simplest and most immediate approach to measuring LTV, but it only takes into account historical data which can limit your ability to predict and plan for changing consumer behavior.
- Predicted value: This metric can be calculated by multiplying your customers’ average spend per year by the average customer lifetime. Or, you can calculate it for individual customers using machine learning models that adjust for seasonality and growth. This strategy can help you predict future spend and focus your efforts on segments that are likely to produce the most value, but it requires robust and sophisticated IT resources.
- Predicted lifetime spend: Predicted spend is calculated by adding the total spend-to-date and predicted value metrics from above. This strategy provides you with the most complete understanding of customer value, but like predicted value, it requires sophisticated data infrastructure, high-quality data, and expert IT resources.
Whichever approach you take, tracking LTV can teach you how to cater to your best customers across every channel. When you segment your customers by LTV, you’re likely to find that the top 20–40 percent of your customers are contributing about 60–80 percent of your overall revenue. This distribution is known as the Pareto Principle, and it’s massively common in small-to-mid-sized brands. Knowing that not all customers provide the same value to your brand, you should be disproportionately investing in these high-LTV customers to drive the maximum return.
By segmenting your customers by LTV and looking at the channel preferences and buying behaviors of the highest-value segments, you can gain a better understanding of the customer experiences that drive the most value for your brand.
For example, which product do your highest-value customers tend to buy first? If you know that the first purchase within high-value segments is usually denim, then you can feature denim in your paid advertising and target lookalike segments for more effective acquisition. For further insight into the buying motivations of your highest-value customers, consider developing a customer survey or poll asking for more information about the shopping experience and customer pain points.
2. Recency and repurchase rates
As most retailers know, time is a huge driver of engagement. The sooner you communicate with your customers post-purchase, the higher the likelihood that they’ll make a second order and the better your retention rates.
However, accurately tracking recency is impossible when your purchasing data is kept in channel-based silos. If you’re only tracking recency on ecommerce, for example, you could end up running a win-back campaign to customers who’ve recently purchased from one of your retail stores.
From an omnichannel perspective, it’s important to not only keep track of when customers made their last purchases, but also which channel they last converted on. Different channels and products may have different repurchase rates, so the timing of your cross-sell and upsell marketing may shift depending on the channel a customer has engaged with most recently.
For more information on calculating repurchase rates and communicating with customers at the optimal time to maximize the second conversion, click here to read our guide, “Loyalty is Lucrative: A Practical Guide to Driving the Second Sale.”
3. Customer satisfaction
Customer satisfaction is a bit trickier to measure than average order value or LTV because it’s a measure of the customer’s emotional response to the interactions they’ve had with your brand. It also requires active input from your customers, so having a good form strategy in place, as well as a tool like Lexer’s Secure Forms to unify form responses with individual customer profiles, is key to successfully leveraging this data.
The most common measure of customer satisfaction is the Net Promoter Score (NPS). Proven to be directly correlated to revenue growth, NPS is measured by sending out a customer survey that asks a single question: “On a scale of 1–10, how likely are you to recommend [brand name] to a friend or colleague?”
Responses to this question are broken down into customer segments by satisfaction and brand loyalty:
- Promoters rate 9–10 and are likely to purchase from you again in the future. These customers are loyal and enthusiastic about your brand, and they’ll likely contribute to your growth through word-of-mouth marketing.
- Passives rate 7–8. These customers are satisfied with their experience with your brand but not as enthusiastic as promoters are. They’ll likely be swayed to purchase by competitive offerings like discounts and giveaways.
- Detractors rate 0–6. These customers are dissatisfied with their experiences and can damage your brand reputation through negative reviews and word-of-mouth.
To get your final NPS score, subtract the percentage of detractors from the percentage of promoters. By analyzing the differences in highly satisfied vs. highly dissatisfied customers, you can begin to understand the ways in which you are missing, meeting, or exceeding customer expectations across channels. Differences in NPS scores by channel—for example, if your most dissatisfied customers almost always shop in-store—will point you to discontinuity in your omnichannel experience and reveal areas for improvement.
To dig deeper and understand the reasons behind satisfaction scores, try sending your NPS survey with additional questions, such as:
- “Why did you give that NPS score?”
- “If the NPS score was below a 10, what would make it a 10?”
- “On a scale of 1–5, how much do you agree with the statement that [brand]’s products are priced fairly for their value?”
- “On a scale of 1–5, how would you rate your shopping experience?”
- “How would you rate your satisfaction with the products you ordered?”
Questions like these will help you get to the bottom of customer satisfaction scores, so you can amend your prices, products, marketing, or other brand elements to improve every channel.
4. Ticket volume
Tickets act as flags to your customer service teams that something has interfered with a customer’s shopping experience. It’s normal for tickets to spike during high-profile events like a major flash sale or when your website goes down, but if you’re seeing consistently greater-than-benchmark ticket volumes, then there are likely improvements that need to be made.
Pay attention to the customer segments that submit the highest number of tickets, as well as the time of day those tickets are sent, the channels through which tickets are submitted, and the types of tickets that are submitted most frequently. If you find that the customers who are submitting the highest volume of tickets also tend to be low-value, infrequent buyers, then you may want to rework your acquisition and growth strategies to disclude them in your targeting. On the other hand, if high-value customers are consistently submitting a high number of tickets, then you need to take a closer look to figure out how to prevent those issues and keep those customers happy.
Being able to combine and analyze ticket volumes and types from every channel is key to developing an impactful omnichannel experience. The support your ecommerce customer service team provides can inform the support your brick-and-mortar customer service team provides and vice versa, so it’s important that your ticket data from each channel can speak to each other to ensure a consistent and satisfactory experience for your best customers across the board.
5. Customer profitability
Customer profitability is a measure of the total profit you earn from a particular customer, taking into account both the gross revenue earned and the associated costs of creating the product and fulfilling orders.
Although customer profitability is a relatively complex measure to calculate, understanding the relative profitability of each customer is extremely valuable for accelerating your growth. A technology partner like a Customer Data Platform can help even small brands with limited IT resources access this measure with ease.
Here’s the basic framework for measuring customer profitability:
- Sales – Returns – Product Costs – Fulfilment Costs = Customer Profitability
This framework is a great place to start, but there are a number of other costs and calculations that you might want to take into account for a more precise measure of customer profitability. For example, the discount rate per customer has an influence on overall customer profitability, and a customer analytics tool can help you incorporate this metric into your profitability measures for more complex analysis.
Using this profitability metric, you can segment your customers based on their margins and lifetime values:
- High-margin, high-value customers are the customers you should focus on first to drive the most profitability. This segment is full of highly engaged customers who buy full-priced products from your brand at a relatively high frequency.
- High-margin, low-value customers are the customers who don’t buy from you often, but when they do, they purchase products at the full price. You can grow the lifetime value of these customers with win-back campaigns, well-timed promotions, and personalized next-purchase recommendations.
- Low-margin, high-value customers are highly engaged and frequent shoppers, but when they do purchase from your brand, it’s typically at a discount. You don’t need to dedicate much resources marketing to this segment, because you know they’ll shop from you when you’re having a sale.
- Low-margin, low-value customers don’t purchase from you often, and the products they do purchase tend to be at a discount. You should avoid targeting this segment in your acquisition and growth campaigns.
Finally, if you inform your profitability-based segments with third-party consumer data such as Experian’s Mosaic, you can learn more about customer motivations and buying behaviors which will help you tailor your campaigns for increased impact. For example, you might notice that your high-margin, high-value segments tend to prefer ecommerce channels, shop for their families as well as themselves, and have highly active lifestyles according to Mosaic. Using this insight, you can build lookalike audiences and target them in tailored advertising campaigns to draw similar high-value customers to your website.
Drowning in data? A Customer Data Platform can help keep you afloat
Traditionally, customer data has been kept in silos based on channels. In-store, ecommerce, and wholesale data was housed in different places, and business applications couldn’t be integrated. This channel-based approach made omnichannel analytics an onerous task that would’ve required extensive IT resources.
Today, the only way to track and analyze omnichannel metrics effectively is by first getting all of your data in the same place and in the same format—and the best way to do that is with a reliable identity resolution tool like a CDP. If you’re interested in learning more about measuring your impact with a CDP, click here.
By stitching together your siloed, channel-based data and attaching it to individual customer profiles, you can take a customer-first approach to data management that quickly reveals trends in high-value engagement across channels. This customer insight gives you a better, more holistic understanding of what your customers want, need, and expect from your brand, so you can begin to tailor the omnichannel experience to maximize conversions across the board.
Lexer’s marketer-friendly CDP can help you access a single view of your customers across all channels. Built for retail, our tools and dedicated support team help you master your customer data at every touchpoint—from marketing to sales to service—so you can deepen customer loyalty and drive profitable growth.