Actionable Insights From APT's Retail Practice

Rethinking Return Policies

March 4th, 2016 | Posted by Jack Parker in Retail - (Comments Off on Rethinking Return Policies)

Returns have always been expensive for retailers, and the number of returns is only increasing with a growing percentage of sales coming through digital channels: in 2014 alone, $284 billion of product was returned. Figuring out how to lower that number without causing customer attrition is a major challenge facing retailers. Should retailers limit return windows? By how much, and on which types of items? Will stricter policies intimidate customers from transacting?

A recent Washington Post article details a study that dove into these kinds of questions, examining how retailer return policies have historically impacted customer behavior. Unsurprisingly, more lenient policies were strongly correlated with higher return rates. These types of policies, however, were even more strongly correlated with higher sales, indicating that customers were more likely to make purchases given the security of a strong return policy.

Based on the study’s findings, it appears that there may be opportunities for retailers to grow sales by making return policies more forgiving. But how will these types of changes actually play out in market? Will customers purchase more in total, netting out returns? Will a more lenient policy increase shrink? If so, by how much?

Rather than relying on intuition or correlations, retailers will need to understand how customers will react before enacting broad changes. The only way to gain this insight is with a Test & Learn approach: test a policy change in a subset of stores, and compare performance to a control group of stores that maintains the status quo. Then, retailers can isolate the action’s true incremental impact on KPIs like return rate, sales, shrink, and customer satisfaction. Using these small scale in-market experiments, retailers can answer the following types of questions:

  • Return Window – What will happen if we extend our return window? Will sales increase? If so, will that outweigh any corresponding increase in returns and shrink?
  • Process – What will be the impact of offering free shipping on returns? Should we move to a stricter strategy for offering refunds to cut down on fraudulent behavior and/or losses from products that can’t be resold?
  • Omnichannel Strategies – How can we profitably allow online orders to be returned in stores?
  • Policy Variation – Are there opportunities to target policy variations to different product categories and customers?

As ecommerce continues to grow and omnichannel customer service becomes more critical, costs associated with returns will continue to eat into retailers’ bottom lines. By testing new ideas, executives can hone in on which return policies will work best for their business.

Join Us at NRF For a Big Ideas Session: Smart Data, Not Just Big Data

January 14th, 2016 | Posted by MHarper in Manufacturing | Restaurants | Retail | Retail | Retail - (Comments Off on Join Us at NRF For a Big Ideas Session: Smart Data, Not Just Big Data)

Join APT this Monday, January 18th for a Big Ideas session about “Smart Data, Not Just Big Data”. We’ll be discussing innovations that retailers are considering today and why it’s important to use a Test & Learn approach to understand whether each of these ideas work. Executives from APT clients will present at the session.

Click here for more information.

Banking Strategies: Top Trends for 2016

January 8th, 2016 | Posted by JDouglass in Financial Services - (Comments Off on Banking Strategies: Top Trends for 2016)

Banking Strategies recently published an article by APT SVP Will Weidman, naming the top trends that FIs should watch in 2016. Weidman says, “2016 is looking to be one of the most transformative years in financial services in decades. Disruptive competitors are growing, digital and mobile continues to evolve, branches look more and more like Apple stores and interest rates have started rising. Banks will need to embrace smart innovation not only to keep up, but to truly differentiate themselves in a cost effective manner.”

Click here to read more (requires subscription).

Strengthening Relationships with Analytics

November 23rd, 2015 | Posted by retailblogadmin in Financial Services | Financial Services | Financial Services - (Comments Off on Strengthening Relationships with Analytics)

Gallup recently published a poll comparing a variety of statistics between national and community banks, which illuminates a few surprising facts. One apparent paradox is that while community banks are more successful at engaging their customers, they lag behind national banks in capturing share of wallet. While customers at national banks keep 71% of their financial products with their primary banks, customers at regional banks only keep 66%. (more…)

How to keep brick-and-mortar retail relevant in the digital age

November 4th, 2015 | Posted by Haley Jackson in Retail | Retail | Retail - (Comments Off on How to keep brick-and-mortar retail relevant in the digital age)

APT Senior Vice President Rupert Naylor recently authored an article published in Real Business titled “How to keep brick-and-mortar retail relevant in the digital age.” In the piece, Naylor comments on the evolving role of the physical channel and how retailers can succeed in the changing landscape. He explains, “With so many innovative ideas on the table and so much potential value at stake, the current retail landscape is ripe for business experimentation. While intuition may lead decision-makers to implement an initiative, its incremental profit impact cannot be accurately measured without first testing the idea with a subset of markets, stores, employees, or customers, and considering the impact in store, online and on mobile devices in a holistic way.”

Read the full article here.

How big data is changing retail and restaurant businesses

October 28th, 2015 | Posted by MHarper in Retail - (Comments Off on How big data is changing retail and restaurant businesses)

APT is featured in an Information Age article on how retailers and restaurants can use big data to gain an accurate view of performance and try new ideas to improve profitability. Click here to read the full article, which includes insights from the APT Index.

Starting from Scratch: How to Build a Billion Dollar Budget

October 19th, 2015 | Posted by Holly Rooker in Manufacturing - (Comments Off on Starting from Scratch: How to Build a Billion Dollar Budget)

The number of companies referencing zero-based budgeting during quarterly earnings calls increased from 14 companies in 2013 to roughly 90 companies in 2015.  With the rise of zero-based budgeting in the CPG industry, how can managers effectively and efficiently make the best budgeting decisions?

Rather than building from the previous year’s budget, zero-based budgeting requires managers to build their budgets each year from the ground up.  This approach forces managers to justify the value of each budget line for the upcoming year.

Proving the value of dozens or even hundreds of initiatives, however, can be difficult and time-consuming.  Running tests in a small subset of stores or markets can enhance the zero-based budgeting process by helping managers quickly and precisely identify the incremental impact of each initiative across functional areas: (more…)

Making Big Data Make Money in Retail

October 8th, 2015 | Posted by MHarper in Retail - (Comments Off on Making Big Data Make Money in Retail)

The importance of challenging conventional wisdom and getting beyond the hype of scale

By Jim Manzi

Any experienced businessperson has seen this movie before with earlier technologies ranging from the World Wide Web to CRM to enterprise data warehouses. It’s the plot in which a technology goes from promise to hype to true application. Big data is now deep into the hype phase of this cycle. All the classic signs are there: You can eat buffet dinners all 52 weeks a year at big data conferences. Big data tag lines are now common in emails from industry analysts, and even investment bankers are tossing around the phrase. But as with these other innovations, there is real substance at the root of the hype. And – like CRM, the web, and data warehouses – big data is a big part of running any large corporation in the future.

Profitably exploiting the emerging opportunity for big data will require using some of the key learnings from companies that have already gone beyond the hype: first, an unwillingness to be snowed by conventional wisdom and technical jargon; second, the ability to act quickly at low cost, learn what works from trial-and-error experience, and then reinforce strengths; and third, a ruthless focus on profits as the success criteria for proposed investments of time or money. Those three characteristics will be necessary as data moves beyond conventional storage capacity and into the cloud. And those characteristics will be critical as retail executives balance the immensity of scale with the practicality of business applications. In short: Big data consists of small data. The challenge is to take the right data and make it drive decisions.

In the end, the transaction data remains the most important. It will show the retailer what makes consumers trade their money for our goods and services. Smart consumer businesses ignore these external data feeds or rebuild their infrastructure around them. Instead they use abstractions to extract most of the analytical value, while only needing a tiny fraction of the data volume.

The thing that is clear is that today – right now – large consumer companies can begin taking advantage of many of these data streams by capturing them at an abstracted level, incorporating them in data schemas, and using them to improve decisions.

The Humility of Test & Learn

Retailers and other executives are aware that data needs to drive decisions rather than drive them crazy. Through careful experimentation to test new programs and approaches, the most serious industry analysts have started to recognize that Test & Learn is central to making big data create value.

A Test & Learn capability for a major marketer requires a specialized analytical platform, but also has several process and organizational components. The starting point is executive commitment. The person or small group with ultimate operational responsibility for shareholder value creation, typically the CEO or president, must legitimately desire reliable analytical knowledge of the business. Second, a distinct organizational entity, normally quite small, must be created to design experiments and then provide their canonical interpretation. Third, a repeatable process must be put in place to institutionalize experimentation as a part of how the business makes decisions.

Here are two examples. First, let’s look at Wawa, a 645-location convenience store chain. Its marketing team had developed a new flatbread breakfast offering that had performed well in spot-testing. Management wanted more robust measurement of what happened to other products when the flatbread was introduced. Wawa used APT’s Test & Learn software to design a scientific test and measure the impact of the flatbread introduction across all key performance metrics and product categories. The flatbread performed well. Unfortunately, the new item was so enticing that it cannibalized sales of existing menu items. Wawa decided not to roll out the flatbread.

Number two: At Subway the debate surrounded whether they should launch a low-cost $5 product. A set of Subway franchisees had implemented a promotion selling their famous footlong sub at $5. While some franchisees were convinced that the promotion was driving incremental sales, others were skeptical. APT’s Test & Learn software compared the performance of franchisees that had implemented the $5 Footlong versus a scientifically matched group of restaurants that had not implemented the promotion. The software showed that the $5 Footlong was profitable, and executives decided to launch the $5 Footlong nationally.

These two examples show companies that have access to a staggering amount of information. They also show two companies that incorporated a systematic method of feeding that data with practical experiments that expand (or manage) key operational and marketing decisions. The systematic focus produced the right data. It cut through the clutter and produced clear results.

Test & Learn, at its heart, is a simple concept for a business promise that is begging for simplicity. The orientation should not be toward big, one-time “moon shot” tests, but instead toward many fast, cheap tests in rapid succession whenever this is feasible. The goal is to build a mountain of pebbles.

4 Steps to Make Money with Omnichannel

August 26th, 2015 | Posted by Katheryn McKee in Retail - (Comments Off on 4 Steps to Make Money with Omnichannel)


APT SVP Jonathan Marek discusses four ways in which retailers can make money with their omnichannel strategies.

Enhancing Media Mix Models with Test & Learn

August 20th, 2015 | Posted by Katheryn McKee in Retail | Uncategorized - (Comments Off on Enhancing Media Mix Models with Test & Learn)

APT SVP Jonathan Marek discusses how Test & Learn can help prove the cause-and-effect relationship between media spend and KPIs.