“Doubloons!” they said. The words crashed gold. “Doubloons!” – ‘Portrait of a Boy’, Stephen Vincent Benét (1917)
Target, Walmart and more recently Amazon – are all r/e-tail giants that have made analytics one of the key ingredients, if not the backbone of their operations as they expand into hitherto uncharted customer segments, geographical territories and business models. So what does that mean for you as a retail giant stepping your toes into the murky data lake with promises of doubloons at the bottom?
One of the key areas that a retail giant with worldwide presence having multi-brand multi-SKU portfolio in its showcase must focus on is optimal management through effective and controlled marketing actions. Ideal marketing actions are a set of marketing campaigns or promotions or any other marketing activity that gives you complete control on each SKU, Hence marketing activity can be used as a lever to achieve exact amount of movement in sales volume or value of a SKU on a particular time period from a particular region in this globe. In order to achieve this one should start by asking the following questions:
Do you know how effective your marketing campaign/promotion was?
- What is the net volume, value and margin impact?
- Did this activity help to strengthen the brand perception?
- Was this activity responsible for cannibalization of any other brand/SKU? If yes, how does the cannibalized amount in volume or value related with the investment in the campaign or reach of the campaign?
BRIDGEi2i implemented a deceptively simple, yet practical analytic approach for a Fortune 100 retail giant with a 1000+ SKU portfolio. The solution helped clearly answer all of questions mentioned above. We wanted to measure effectiveness of various trade & consumer promotion on trade revenue with wholesalers, convenience stores and retailers, segregating impact of price change, promotion, competitive actions, cross SKU cannibalization & Halo Effects.
The process involved:
Know your SKU’s behaviour:
The most important thing in CPG business to know the behaviour of all active SKUs. One should know the profile of purchasers who purchase those SKUs and their purchase frequency. All these SKU’s can be grouped based on their customer profile and purchase trend. The idea is to bring down the large number of SKU’s to a set of manageable number of group.
Know your shop’s behaviour:
In a similar way in retail business all outlets can be segmented to identify smaller unique number of entities in which every outlet is homogeneous but very different from other group member. Segmentation can be done based on the profile of customer who visits the outlet, their frequency, their purchase pattern.
Understand default trend and seasonality in business:
In the process of segmenting the SKUs or retail outlet one must have gone through the exercise of understanding their sales pattern. When I’m saying understanding sales pattern meaning primarily understanding the normal sales trend and seasonal effect.
Track all marketing spend and campaign period:
Track start and end of each marketing campaign, campaign objective, cost, target population and effectiveness in terms of reach or footfall or uptake.
ROI analysis, Market Mixed Model and Cross Validation:
We can perform an ROI analysis for each marketing campaign after the completion of a campaign and this analysis can paint a picture at broad level regarding the success and failure of the campaign. Assessing effectiveness of a marketing spend based on a simple ROI analysis might be misleading because of two primary reasons one the impact is not due to only because of this campaign there might be other marketing campaign impact on it positively or negatively and two impact duration is not quite known.
A better way to fit linear regression model to measure the impact of different kind of marketing spend on sales. The model will basically estimate the sales at a given marketing input scenario. There will be interaction effect in the model for sure as two or more campaign drives together the impact on sales. It’s an important exercise to derive back the individual elasticity i.e. interaction effect should be taken care of while building the model. Model coefficient for each marketing spend is the indicator of elasticity and this coefficient can be used to estimate return of a particular marketing spend / campaign.
Validation is another key exercise once model is built. One needs to examine that the impact is valid enough with in a same defined product or outlet or customer segment. Key findings from the validation exercise would be to identify the significant change in mix (product/retail outlet/customer) hence identification of pseudo positive impact. Sometimes it might happen that model might estimate correctly the impact of all marketing spend at overall level but not able to capture the phenomenon with in a segment. Though it’s not mandatory but good to have the robustness at each segment levels as we know each and every campaign are driven to keep a particular objective and target population in our mind.
Optimize Marketing channel spend based on ROI from each channel:
Once the impact of each campaign or each channel is known then it’s not a big deal to control them. Optimization techniques can be applied to control marketing spend in order to optimize maximum return.
How did we do it?
BRIDGEi2i has already proven its expertise in successfully deploying solution which helped it’s customer to control marketing spend across the channel and budget allocation for a particular campaign.
- Estimate the base sales and incremental effect for a marketing vehicle.
- Estimate contribution for individual vehicle towards revenue.
- Compute average and marginal ROI for marketing spend in each vehicle.
- Directional recommendation of changes in marketing mix and incremental ROI.
- Impose preset constraint for a particular marketing campaign or vehicle while optimizing budget allocation to curtail the negative impact like cannibalization, depreciation in perceived brand value.
This blog is authored by Sandeep Kumar Paul, Analytics Consultant at BRIDGEi2i
About BRIDGEi2i: BRIDGEi2i provides Business Analytics Solutions to enterprises globally, enabling them to achieve accelerated business impact harnessing the power of data. Our analytics services and technology solutions enable business managers to consume more meaningful information from big data, generate actionable insights from complex business problems and make data driven decisions across pan-enterprise processes to create sustainable business impact. To know more visit www.bridgei2i.com
The views and opinions expressed in this article are those of the author and do not necessarily reflect the official position or viewpoint of BRIDGEi2i.