Trade Spend E-Book
“Winning The New Age Customer”
By Relational Solutions, Inc
March, 2015
Contents
Executive Summary ....................................................................................................................... 3
Our View of Maturity Curve and the Journey ............................................................................... 4
Maturity ........................................................................................................................................ 4
Key Implementation Challenges in this Journey ........................................................................... 6
A transformational view of a Post Event Analytics tool................................................................ 7
Data & Analysis Readiness Assessment ........................................................................................ 9
Multi-Level Data Integration ......................................................................................................... 9
Reporting & Insight Delivery ....................................................................................................... 10
Pre Event Analytics...................................................................................................................... 11
By Relational Solutions, Inc
March, 2015
Executive Summary
Trade promotion spend, the largest spend after COGS can account for as much as 25% of gross sales and
is the one that typically overshadows other segments of a Consumer Products (CP) company’s marketing
budget. A Nielsen study observed that 55% of trade promotion spending fails to benefit either the
manufacturer or the retailer. Management consulting firm Bain & Company goes even further, citing other
studies that estimate up to 90% of trade promotions are simply not profitable. Given the extent of this
spend and its direct linkage to profitability, it becomes imperative to track the impact of it and the
resulting profitability very closely.
Few commonly acknowledged business challenges:

Inability to understand promotion efficiency leads to companies not able to allocate resources to the
correct promotion, as they cannot systematically distinguish between profitable and loss making
promotions.

Trade promotions can cause retailers to stock up on goods, without passing the savings on to
customers.

Excessive promotional activity may wreck the supply chain, by creating artificial peaks and valleys.

Sometimes trade promotions benefit the manufacturer but not the retailer, particularly if the
promotion cuts into profits from other higher-label brands, straining the relationship and mitigating
future buy-in.
Few questions that an exhaustive PEA tool and program looks to answer:

Can we have a historical view of all promotions executed for a product/brand?

What are the key metrics to measure the success of a promotion?

Can we compare the performance of a promotion with respect to past promotions?

Can we identify which customers are using my promotions better?

How is the acceptance of promotions across customers? Are there similarities or differences in the
acceptance levels based on products or promotion typeset?

Can we predict the impact of promotions on sales uplift and ROI?

Can we customize promotions for different customers based on their sales behavior?

Can we identify which factors contribute to the success or failure of a promotion?

Can End Consumer insight help me in customizing my promotions for better acceptance and
effectiveness?

Can we identify how much should be spent on a promotion?

What are the levers that help me maximize my sales and minimize the costs of promotion?
By Relational Solutions, Inc
March, 2015
Our View of Maturity Curve and the Journey
Trade Promotions Journey broadly runs on three phases Planning, Execution & Evaluation. A glimpse into
what these cover is depicted below
Figure Error! No text of specified style in document.-1: Trade Promotion Journey
We can see that the maturity level of a CPG company to execute Trade promotions will span across the
three phases and Data & analytics will aid in moving up the maturity curve.
Maturity
By Relational Solutions, Inc
March, 2015
Figure Error! No text of specified style in document.-2: Maturity Details
As CP manufacturers move from basic to optimized stage, the incremental benefits derived increase too.
These can be in the form of improved profitability by rationalizing promotion spends, avoiding overlapping
promotions, choosing more effective promotion vehicles by granular dissection of store types, considering
shopper profile while designing promotions, etc. It can also be improved collaboration with retailers to
design promotions such it not only benefits the manufacturer but also drives retailer’s profitability
through effective Joint Business Planning.
Fast tracking of incremental benefits from this program require various support mechanisms. These can
be in the form of organization capabilities like having a dedicated team to provide insights as seen in the
advanced stage of the roadmap, or having IT tools and systems that automate the process of planning and
evaluation, and provide predictive analysis as we move to optimized stage of the journey. The need for
information too would increase as we move ahead.

Stage one will perform analysis of the shipment sales data, the COGS, and the promotion
investment to come up with basic ROI calculation.

Stage two stage would warrant analysis based on POS and secondary sales data, and

Stage three would bring in the need for analysis based on competitor data, and even shopper
data.
Most CP manufacturer’s trade promotion operation effectiveness are in various stages of maturity (above
listed three stages) across various regions across the globe. Many use spreadsheets, home grown systems
or CRM software with basic capabilities, generating some basic analytics. In addition, many CP
manufactures use different tools for different geographies causing inconsistent non-standard KPI’s and
metrics.
By Relational Solutions, Inc
March, 2015
For companies to move into the advanced and optimized stage of analytics, they would need a robust tool
for its PEA process, as well as data to come up with key insights critical to optimizing future plans.
Promotion planning data would be sourced from their internal and the external data sourced either
directly from the Retailers (POS), or procured from IRI or Nielson. This set of data can then be loaded into
the PEA tool to automate the process of analysis, and generating near real-time insights.
Key Implementation Challenges in this Journey
Excellence and optimization in trade promotions area needs for both Post event and Pre event analytics
data with the feedback loop between the two to aid in better execution and sustainable returns.
Some of the typical data and implementation challenges while rolling out a Post Event Analytics Solution:
Adding to these we also need to address challenges in:

Missing Organization wide analytics capability- The ability to dig deeper into the data and provide
right insights in a timely and regular manner is a huge gap in most of the CP companies. This leads to
o
Extended lead times on Insight Generation
o
Inability to connect the dots
o
Losing market competitiveness
o
Inability to execute
Missing feedback loop – while there are insights generated in pockets at different frequencies, these
insights are not actioned at the right time to drive better business results. This is also due to the inability
to connect the dots and have the big picture view as well as organizational readiness to use Data
analytics to aid business
By Relational Solutions, Inc
March, 2015
A transformational view of the PEA tool
Based on the implementation and organizational challenges stated above, it is evident that a
transformational PEA solution needs to be a combination of Strong Data Integration layer, a highly user
friendly reporting layer and a robust analytics & Insights layer as depicted below.
Post Event Analysis should not be looked at as a standalone solution rather there should be a closed-loop
process and integration including data exchanges between the Pre Event Analysis and Post Event Analysis.
We believe “best practices” are drawn from rich experience of trade promotion management
implementations and covers a wide range of functional and technical areas. In trade management
analytics, Relational Solutions, Inc. has implemented a broad portfolio of analytical solutions – helping
companies define the best allocation of promotion investment across components such as price (e.g.,
EDLP, TPR, etc.), merchandising, in-store promotion, production assortment optimization, compliance,
etc. Our approach typically includes working with syndicated data (e.g., Nielsen, IRI) and retailer POS and
performing special data transformations to establish relationships that measure phenomenon such as the
impact of depth, frequency, and duration of promotion, as well as diminishing returns of promotion spend
and decay over time. Below are a few high level “best practices” we believe should be the core
components of a Post Event Analytics Solution:







Integrating internal spending and retailer POS to compute customer-event profitability
Providing customer-event level scorecard KPIs (e.g.., incremental lift and ROI)
Incorporating cannibalization/halo and pantry loading/forward buy calculations
Using clustering analysis to identify best vs. worst performing events (and why)
Comparing performance and helping reallocate across accounts, products, tactics, etc.
Next generation of econometric model-driven marketing return on investment measurement,
fact-based planning and causal forecasting, and media-mix optimization.
Data diagnostics and visualization
By Relational Solutions, Inc
March, 2015


Econometric marketing mix model building and management; fact-based planning utilizing
optimization and what-if scenario capability.
Econometric models that can be used for both historic “what would have happened” analysis as
well as for forward looking planning.
As a leading CP technology and solutions company, Relational Solutions, Inc. has the capabilities to
integrate the combined analytical processes, organization, and tools (inclusive of specialized third party
offerings) required to support effective delivery of improved return on trade spend investment. Though
the best practices involved may sound like commonly used analogies, the real differentiation is in terms
of the project execution itself and the resultant business recommendations. Below is a snapshot of the
methodology.
The “Post Event Analysis & Optimization Methodology” steps are listed below in detail:
1. Data & Analysis Readiness Assessment
2. Multi-Level Data Integration
3. Event Insight Generation
4. Building Predictive Models
5. Trade Promotion Optimization
By Relational Solutions, Inc
March, 2015
Data & Analysis Readiness Assessment
Analyzing every problem statement on Trade Promotion needs to kick start with the right and correct
data. Data readiness and maturity assessment phase has Relational Solution’s pre-built PEA framework
accelerators (with defined set of rules and algorithms) that help propel the data harmonization and
thereby allowing you to spend more time on analysis to provide the best business insights. As listed above,
saving a huge chunk of time is the primary benefit of this phase along with process compliance to solve
data inefficiencies.
Some of the key deliverables in this phase include a data audit document, categories/customers mapping
document to convey feasibility & data maturity and data mapping to reveal the suitability of analysis for
PEA in each country
Multi-Level Data Integration
Integrating multiple data sources (Structured/Unstructured, Internal/External) is one of the major
challenges of PEA. Rich data always forms the basis of richer insights and it is an absolute mandate to
possess the expertise to integrate the data in the right way. Though data integration is a mandate in the
longer run, the initial exploratory analysis can be performed on the data to understand the product/outlet
behavior and how the promotions are performing. This understanding helps in building the integration
layer in the right way. Our recommendation would be to start off with an initial PEA analysis and
assessment and then use it as the base to build the integration layer.
Relational Solutions’ TradeSmart solution addresses all these issues and the features of our solution
include:
By Relational Solutions, Inc
March, 2015






Data Integration, Cleansing & Harmonization
POS Integrator with Pre-built retailer mappings
Customizable business rules, POS Cleansing and validation routines
Integration objects for Oracle, SQL Server, DB2, Excel, ODBC, OLEDB, Teradata, Neteeza, SAP, SAP Hana, RL, txt,
FTP, Access, Nielsen, IRI, NPD, etc.
Flexible Data model – Design/Retail Calendars/Report Matrix
The Pre-Event Analytics though is dependent on the integrated data, for understanding the product/outlet
behavior and how the promotions are performing an exploratory analysis can be conducted to build
hypothesis and get started on the advanced analytics journey. This understanding also aids in building the
integration layer in the right way.
Reporting & Insight Delivery
While integrated data hub is one part of the Post event Analytics, generating the right KPI’s and delivering
them through the right charts and graphs to ensure consistent insight delivery is the other portion.
The reports created will allow users to view the promotion performance across “As-Is” and “As-Was” as
retailers change via acquisition or a change in hierarchies, and promoted product groups change over
time.
By Relational Solutions, Inc
March, 2015
Pre Event Analytics
Event Insight Generation
The analytical data mart is ready to be consumed post data integration. The next step in the process is
generating business insights through exploratory data analysis and the promotion post event KPI’s. The
PEA framework also has a prebuilt segmentation methodology that used to classify the Outlet/SKU’s that
show similar behavior. This classification forms the basis for “Trade Promotion Optimization” and impacts
each level of analysis, insights derived and the recommendations.
Post Event Analysis report will consist of the top priority insights that need immediate attention from the
business and recommendations on how to tackle those business challenges. All the insights and
recommendations will be a part of the detailed TPA report that would also recommend the best
promotion plan to execute
Apart from this, all TPA KPI’s will be captured using interactive dashboards for every level of business users
to consume and make priority decisions on-the-go.
Building Predictive Models
Building predictive models has become an integral part of the PEA framework as it gives us a glimpse into
the future and plan out promotions accordingly. All statistical models behind the segmentation, What-If
lift prediction and ROI forecasting, helps the planning team and the category/brand managers to plan the
next promotional calendar effectively. It is the actionable business insights and the Predictive Analytics
based WHAT-IF simulation that will drive increased forecast accuracy.
These models and the output will be part of the detailed PEA report that would also recommend the best
promotion calendar and next best actions (NBA’s.)
By Relational Solutions, Inc
March, 2015
Relational Solutions, Inc.
Based in Cleveland, Ohio since 1996, Relational Solutions is a software and service company
specializing in data integration for CPG manufacturers. Our SmartSolution foundational
architecture allows for growth and change to provide better business intelligence and insights
for today and the future.
POSmart is our Enterprise Demand Signal Repository. It expedites the integration, cleansing and
harmonization of point of sale data with syndicated, third-party and internal data for a holistic
view of sales. POSmart improves retailer relationships, streamlines internal efficiencies,
decrease OOS's, and maximizes profits.
TradeSmart and PromoPro.
TradeSmart leverages the Smart Solution Architecture and it’s ability to automate the
integration, cleansing and harmonization of various trade components required to accurately
measure trade spend ROI. It lets you start measuring promotion performance as the promotion
is going on.
It brings together promotion plans, shipments and consumption as it relates to trade
promotions. Promotion plans may be in Excel, SAP TPM, Demantra, Siebel, Prescient or other
source. It brings together plans with shipments and consumption is what gives TradeSmart the
ability to accurately measure ROI for both the manufacturer as well as the retailer.
It offers the ability to not only accurately, analyze the trade promotions but it also lets you
compare planning expectations across all retail segments. Users can understand whether
promotions were properly executed along with retail compliance. It also provides a common
repository for all historical promotions, enabling multi-year analysis and comparison of trade
spend initiatives. Results from TradeSmart can be fed back in to other systems.
PromoPro shows a cross section and represents all relevant consumption, shipments, trade
plans and competition within a promoted product group and fiscal year for a given retailer or
banner. Users can group together promotions into an event for analysis. Users can also make
edits to properly align promotions.
For more information on POSmart, TradeSmart or PromoPro:
Contact
Relational Solutions
www.relationalsolutions.com
Sales: 440-899-3296 x229 or x225
By Relational Solutions, Inc
March, 2015