Measuring the overall effectiveness of offers is often a struggle. Whether assessing in-store circulars, digital coupons, direct mailers or other vehicles, the key question is how to ensure promotions are effectively driving total value for a pharmacy. https://youtu.be/57ghR94SYXM

1. 1
GUIDE TO:
PROMOTIONAL ANALYTICS
IN TODAY’S RETAIL WORLD
INSIDE YOU’LL FIND OUT:
The real barriers to effectively
measuring promotional performance
How to use the granularity of data to
drive better offers
How to account for total store metrics
in your promotional strategy

2. 2
Promotional Analytics in Today’s Retail World
Circular, coupon based, and digital promotions
generate a lot of data at a very detailed level. For
one, there are endless permutations of program
attributes that can be parsed out for analysis. For
example, was an item featured on the front page,
back page or themed section of a circular? How
many different versions of an online offer were sent
out by geo-location and by customer segment? Was
the item in question grouped with complementary
items as part of a themed feature?
If you’re the category manager for outdoor products
and you’re trying to decide how best to promote
lawn chairs, you might want to compare a variety of
past promotions. For instance, how did lawn chairs
perform when they were featured alongside outdoor
tables, charcoal grills and charcoal briquettes versus
the time they were featured alongside mosquito
repellent, sunscreen and garden hoses instead? How
many shoppers did one version of the offer reach
compared to the other? What was the total margin
associated with each scenario and how much of a
halo effect did it have across the store?
Promotions continue to be an important initiative
in retail but measuring their overall effectiveness
remains a barrier. Knowing what a promotion’s
full impact is on the total business is what
differentiates leaders from laggards in retail.
Basket-level analysis is necessary for understanding promotional
effectiveness but it is often a time-consuming, manual process.
1. USING ALL RELEVANT DATA IN YOUR PROMOTIONAL ANALYTICS
ANALYTICS FOR ITEM-LEVEL PROMOTIONS
You know that printed weekly paper that shoppers pick up from a rack at the front of a store when they walk
in? These flyers play an important role in the shopping experience for many customers. In retail parlance, this
flyer is often referred to as the circular. Similarly, there are coupons in the Sunday newspaper (known as free
standing inserts or FSI); offers mailed directly to shoppers at home (referred to as direct mailers); and digital
offers that retailers send to customers via mobile apps, email or social media. These promotions are integral
to the business strategy of most leading retailers. Given the importance of such promotions, it might be
surprising to the casual observer that retailers often struggle to measure their effectiveness.
The main reason for this challenge is that promotional data often sits in silos, preventing access to a
comprehensive view of detailed data. Additionally, basket-level analysis is necessary for understanding
promotional effectiveness but it is often a time consuming, manual process. But as retailers look to adapt
to the fast-changing retail landscape, they are realizing they must get better at conducting promotional
analytics if they are to survive. In this guide, we lay out three key focus areas for retailers looking to improve
how they analyze their promotions.

3. 3
Promotional Analytics in Today’s Retail World
These are the types of questions that a retailer
and their suppliers would want to explore in order
to optimize their promotions. In an era where
promotional budgets are vulnerable to increased
scrutiny, it’s crucial for business professionals to
be able to answer questions about every element
surrounding a promotion – from discount price to
margin impact to trips driven.
Getting every component of a promotion into a
format that’s ready for analysis requires pulling the
data from the various places and then organizing as
needed. Why is this more difficult than it sounds?
For starters, promotional data lives in many different
places. Sales data is often captured by POS systems.
Coupon redemption is often handled by an outside
clearinghouse or agency. Promotional calendars are
often tracked on spreadsheets, separate from POS
data. Store participation data might live in a separate
system that may or may not include all the divisions
in a standardized view...and so on.
Once all the data sources are identified, the process
of bringing it all together can be manual, especially
if analysts lack the means to consolidate everything
efficiently. So while it’s inevitable that detailed data
will continue to be generated in large volumes, the
old ways of wrangling promotional data are no
longer adequate. A more efficient and automated
way to gather data is necessary.
WHAT PROMOTIONAL DATA IS RELEVANT?
Many different types of detailed or granular promotional data are generated
by a circular, FSI, direct mailer or digital offer. Some of these are:
Date range – can vary from a week to a month
Amount of product shipped to support a promotion
How many and which stores participated in a specific promotion
Which regions participated in a direct mailer effort or were covered by an FSI,
online coupon or social media offer
Detailed information on past promotions for comparison
Location of item in a circular or mailer – front page, themed page, back page, etc.
Size of an FSI – full page, half page, third page, etc.
Size and placement of a digital coupon
Adjacencies – other items or categories either featured with the primary item or
benefiting from the primary item’s promotion

4. 4
Promotional Analytics in Today’s Retail World
No doubt every retailer by now agrees that having
strong analytical capabilities is table-stakes in today’s
highly competitive retail environment. As ecommerce
retailers demonstrate their ability to operate and
iterate on a second-by-second basis, it’s important to
recognize the role of analytics in their success. When
it comes to promotions, it is no less important to
apply advanced analytics than to any other business
initiative. Arguably, it is even more important –
the sheer annual spend behind retail promotions
continues to reflect the influence of value-conscious
customers.
For years, retailers and suppliers have had access
to promotional performance metrics, but the data
is often available only in aggregated or summarized
form. Promotional details are sometimes lumped
together into one bucket, regardless of the type
of promotion involved. For example, if an item was
included in an in-store circular, it might be counted
as a feature. But what about direct mailers? These
reach the shopper in a different way than in-store
weeklies; yet, they might also get tagged as features.
The same aggregation can happen with FSIs or
digital offers. But because each of these reach a
different audience at a different point in the shopper
journey, it’s important to be able to disaggregate and
measure them separately. What works for a shopper
via an in-store circular may not work via a direct
mailer or online offer.
Reaching the right customer with the right
promotional offer is dependent on a company’s
ability to accurately measure the performance of
different types of offers. Almost as important is the
ability to test, learn, and iterate fast, which means
being willing to try different takes of an offer very
quickly. Not only does it inform budget allocation
decisions in the short term, it also helps retailers
better understand their customers in the long
term. This is easier to do if you can assess how a
promotion is performing within days of launch, rather
than weeks or months after the promotion is over.
Having a limited view of promotional details can
obscure inefficiencies.
Which Metrics Matter?
What do retailers need to know about a promotional
offer beyond sales lift by item? For starters, a critical
metric is the halo effect of a promotion. What do we
mean by halo effect? It is the impact that one item
has on the sales of items around it or associated
with it. This is an important metric to understand
because a store gains a lot from a promotion’s
ability to drive sales of other items, especially in
adjacent categories. In a circular, this becomes even
more nuanced because of the way a circular can
be built from scratch. An item can be grouped with
others, so that the shopper is visually guided to a
theme or a grouping. And because of the nearly
endless combinations of items that can be grouped
in a circular, it’s important to compare different
groupings.
What do retailers need to know about a promotional offer beyond sales lift
by item? For starters, a critical metric is the halo effect of a promotion.
2. GETTING GRANULAR - WHY DETAILED PROMOTIONAL ANALYSIS MATTERS

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Promotional Analytics in Today’s Retail World
As an example, let’s say a popular brand of soda is
promoted at a hot price point on the front of the
circular and drives strong incremental lift. This might
be considered a successful circular feature. But upon
closer look, it turns out the soda does not drive
bigger baskets. In fact, most baskets associated with
this promotion only contain the soda and maybe
one additional item, barely reaching $5 per basket.
Shoppers end up “cherry picking” or stocking up
because of the discounted price. Also, the discount is
so deep that, despite a strong lift, neither the retailer
nor the supplier make much profit.
In contrast to the soda example, let’s say a brand
of tortilla chips is promoted in a circular at the
same retailer. It has a shallower discount and drives
lower lifts, but it’s featured in a game-day theme;
the average basket containing those tortilla chips
also contains an avocado, a jar of salsa, two fresh
tomatoes and a 2-liter bottle of diet soda, for a total
basket ring of $12. That’s quite a different impact
than the soda promotion! Yet, you would not know
this simply by looking at the lifts generated by each
promoted item. And you might not know how the
layout of each promotion impacts the performance
of the item – or its halo effect on other items –
without the basket-level detail.
Driving Total Basket Size
Front Page
Soda 6-pk Promo
Standalone feature
(no theme)
Strong lift
Avg basket: $5
Lift
$
Stock up
effect
Halo
effect
Cost of
promo
True
value
of soda
promo
Middle Themed Section
Tortilla chips promo
Grouped with game-day
theme snack items
Medium/avg lift
Avg basket: $12
Lift
$
Stock up
effect
Halo
effect
Cost of
promo
True
value of
tortilla
chips
promo
Reaching the right customer with the
right promotional offer is dependent
on a company’s ability to accurately
measure the performance of different
types of offers.
Measuring a promotion’s impact on the total basket $ is key

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Promotional Analytics in Today’s Retail World
The following example on the right highlights
the difference between promotions that drive
stock-ups and those that drive trips. Say you
have a promotion that drove lots of incremental
units but the same number of trips as when the
item is not on promotion. Then you modified
the promotion, and maybe it drove fewer
incremental units but it drove more trips. If you
know the size of the basket, you would know
which promotion drove more total dollars for
the store. Assuming basket size stays about
the same, the promotion that drives the most
trips is more effective because it drives more
total dollars for the retailer. You could then
investigate what was different between the
promotions to help you decide on which one to
repeat in the future.
With countless promotion types, time periods
and metrics that matter to the business,
measuring the performance of a promotion
at the full store level requires the flexibility to
analyze multiple iterations quickly. Doing this
manually in a spreadsheet is unrealistic because
it is highly time consuming. That is why retailers
often cannot see beyond the item or even the
immediate category. The pace at which retail
is moving today makes these ways of working
obsolete. That is why conducting analytics at a
granular level but in a scalable way is a must-
have competency for retailers today.
WEEKLY SALES REGULAR PROMO A PROMO B
Units 50,000 125,000 100,000
Unit price $3.00 $2.00 $2.00
Basket $25 $25 $25
Trips 50,000 50,000 75,000
Units/trip: 1.0 2.5 1.3
Total item
spend/basket:
$3.00 $5.00 $2.67
Balance of
basket:
$22.00 $20.00 $22.33
Total unit $: $150,000 $250,000 $200,000
Total basket $: $1,250,000 $1,250,000 $1,875,000
Total balance
of basket $:
$1,100,000 $1,000,000 $1,675,000
Which Promo is More Successful?
Hint: which promotion drove the most
trips, the most total basket $’s, and the most
balance of basket $’s?
3. MEASURING THE FULL STORE IMPACT
With the soda vs. tortilla chips example, we demonstrated how a savvy retailer – equipped with the right
view of data – is able to see how an offer impacts the size of the basket. Similarly, the impact of a promotion
on store traffic can make a big difference to the retailer at the total store level.
With countless promotion types, time
periods, and metrics that matter to the
business, measuring the performance
of a promotion at the full store level
requires the flexibility to analyze
multiple iterations quickly.

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Promotional Analytics in Today’s Retail World
MAKING YOUR PROMOTIONAL DATA WORK HARD FOR YOU
Promotions continue to be a powerful vehicle in today’s retail world. The most analytically advanced
retailers and manufacturers use analytics to understand every aspect of their business, including
promotions. The winners will be the ones that use data to understand how their promotions impact trips,
basket size and sales of adjacent categories.
For businesses looking to take the next step in managing their promotions, 1010data can help. With years
of experience in the retail industry, 1010data’s Insights Platform offers promotional analytics solutions that
are intuitive, flexible and fast. The Event Group Lift History tool, for example, allows you to examine past
promotions at a detailed level for a particular set of items. It breaks down event code data by shopper
segment so you can use it alongside loyalty data or other customer data. The interface is as simple and
familiar as a spreadsheet, making it easier to slice and dice your analysis as needed.
1010data also offers the Circular Optimization tool, which is designed to conduct iterative “what if”
scenarios for proposed offers. With this easy-to-use tool, you can compare different elements of a circular
promotion. In addition to understanding sales lift, you can use the Circular Optimization tool to quickly
assess a promotion’s ability to drive more trips, larger baskets or halo margin. Throughout this guide,
you’ve seen various examples of how detailed analysis can lead to more impactful circular offers.
Whether measuring the effectiveness of circulars, direct mailers, or digital offers, 1010data’s promotional
analytics capabilities can be applied to any type of promotional vehicle. Custom solutions are available
and easy to develop in days, not months or weeks. The greatest value of this capability is the ability to
analyze offers at a more in-depth level without slowing down your business.
1010data also offers the Circular Optimization tool, which is designed to conduct
iterative “what if” scenarios for proposed offers. With this easy-to-use tool, you can
compare different elements of a circular promotion.

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DRIVE MORE TRIPS AND BIGGER BASKETS
WITH PROMOTIONS
1010data can help retailers make better use of their data to measure and optimize offers that
drive total value at store level. With promotional analytics solutions that fit each company’s
needs, 1010data can help retailers:
Incorporate all the relevant promotional data into a simple-to-use interface
Conduct more in-depth promotional analysis by leveraging the granularity of data available
Understand how each promotion impacts trips, baskets and adjacent categories
Generate “what if” scenarios to make better decisions about future promotions