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One of the most salient metrics used in retail today is the customer lifetime value of a business.

Waiting with flowers
Photo by Simon Hattinga Verschure / Unsplash

Even before financial projections and budgeting exercises, we see more and more retailers use this metric as a proxy for long-term sustainability of the business.

Thanks to the proliferation of measurement tools and better data science techniques at our disposal, we have littered our retail dashboards with metrics around the customer.

From average frequency between visits to social media mentions, we can now use different metrics as proxies for customer lifetime.

We've always known that customers were vital to retail.

What makes 2019 so different?

Today, we now that we of its importance, we can now learn how to better measure our efforts, scale them and predict their impact.


Measurability

Previously, due to the limitations of tracking tools, we could never attribute our customer support efforts to actual revenue impact.

Every ticket answered or conversation struck up has traditionally been viewed as an expense.

We've always had kept it under the pile of metrics because it was always easier to track metrics like "Average Order Value" and "Average Number of Transaction" on our retail dashboards.

Now, we know the impact of a:

  • Negative NPS score
  • Bad review on Facebook
  • Bad checkout experience

We can finally quantify it.
With internal statistical analysis, we now know that a bad delivery package could shorten the lifetime value by as much as X%.

Cute piggy bank
Photo by Fabian Blank / Unsplash

Why is all this important?

Financial Justification.

It has always been difficult to get budget for new initiatives, especially those that might or might not have attributable impact to the bottom line.

Better measuring technology allows us to justify spending $10,000/month on our customer support software because the impact of a bad experience could actually cost the company upwards of $1,000,000 a year.

(Note: The reverse is also true. We can now also quantify the marginal impact of a great shopping experience)


Scalability

Another major difference today is the rapidly decreasing cost of engaging with customers.
This means we can scale it.

In the past, engaging with customers meant speaking to them face-to-face one at a time. Frontline staff played a crucial role in this (and still do), but it was hard to scale the investment in this department because cost (mostly manpower cost) rose linearly with every new hire.

Photo by Ryan Franco / Unsplash

Enter the age of software

Today, a customer support rep. can take on a dozen emails in his inbox just by himself.
He can refer 30% of those request to a pre-built FAQ page or a order-tracking page without having to dive in too much for each customer.
He can escalate issues across various departments in a matter of seconds and resolve complex issues (such as a mistake in logistical arrangements) within a few minutes.

All without having to leave his seat.

Why stop there?

Now that we know the actual impact of customer satisfaction, why go on the defensive? We can now start proactively engaging with our customers.

Why not invest in a social media analytics tool?

  • Learn what people are saying about you
  • Figure out how the general sentiment is changing
  • Reach out to delight!

Predictability

Tied to the first point on measurability,

Predictability encompasses replicating previous successes and avoiding past mistakes

It all starts with measurement of an experiment.

  • A new landing page thats more accessible or;
  • A new marketing campaign to engage loyal shoppers

You can start with small experiments and test your hypothesis against just 10% of your entire shopper base.

Once you have a winner, software has allowed retailers (even those that traditionally don't have coders in the room), to scale their experimentation efforts up to their entire consumer base.

How do we predictability guarantee success?

There are a few steps to follow here-

  • Start with a hypothesis
  • Segment your shoppers
  • Run test
  • Deploy to the most successful experiment
  • Record results + Learning points
  • Repeat next month (or week depending on your scale)

Why is this possible today?

Better segmentation.
We know more about our shoppers today than we ever did and many expect us to use this information. VIP shoppers don't want the usual checkout, they want to red-carpet treatment where products are delivered within the next day.
They don't want to be treated with the usual advertising materials, they want email newsletters tailored specifically to them.  
Segment your experiment group.

Investments into experimentation and analytics.
It is not enough to simply run the experiment without a clear hypothesis behind the experiment or the proper tools in place to track those metrics. Imagine running weekly email campaigns without tracking and analytics tools in place to track the ROI of those emails.
It is a VERY costly investment to constantly be churn out email after email and 8 weeks later realize that you have no idea what made an impact.


Closing words on Customer Value

Start tracking this metric.

Place it in the center of your retail dashboards if you are in a management position. Don't get caught with your pants down because your shoppers all start suddenly leaving you.