09th Apr, 2020
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What are my competition’s misses which I can hit?
How can I be prepared for emerging trends?
How do I make my sales go from ‘MEH’ to ‘BOOM’?
Am I leveraging optimal technology solutions in my business?
These are probably the few topmost and constant questions that run in the minds of retailers, that too in a loop.
If seen closely, it is the last question that leads to that one answer which suffices all these questions.
Technology giving the retail industry a face-lift may be regarded as an understatement since we are aware that the dynamics are changing from grand to a granular level. It can be likened to a situation of shifting sands where the question is no more only about online vs. instore or competitive pricing or all-time availability, rather, the consumer quest now goes much beyond that. The new-age consumer looks for a captivating experience. And there comes in the role of mighty technology!
Modern retail is the scientifically evolved avatar of its erstwhile version which was more traditional in nature. Be it the leverage of artificial intelligence, machine learning or the incorporation of 3D holographic techniques, the industry has come a long way. After all, the present time demands a nimbler approach to quick and informed decision-making which is driven by data-logic and automation. Out of all the trends so far, the one which is gaining extensive traction these days is the leverage of advanced BI analytics in retail.
Precision in analytics relies upon data and retail is a domain which literally churns out gigantic amount of data every day, every minute. Be it the sales data, footfall figures, online product view etc. – the sector just never stops streaming data. This justifies the mammoth industry trend, which retail analytics has become.
Going by the statistics as well, the global retail analytics market is expected to grow from USD 3.52 billion in 2017 to USD 8.64 billion by 2022, at a Compound Annual Growth Rate (CAGR) of 19.7% as per a recent research done by Markets And Market
Merchandising Analytics – The New Focus
While sales, marketing, risk management, consumer engagement, supply chain optimisation etc. are all critical elements of the retail function wherein analytics is altering the conventional paradigm, it is the merchandising analytics arm which is seeing maximum traction – and for all the right reasons.
A typical sales journey begins from the moment a prospective customer sees a product promotion signage or the product in the display, the journey continues as he walks past the shelves looking at the products. The motion continues even as he reaches the payment counter and looks at the desk-kept products/ accessories while making the payment. It is those few minutes which the retailer has to stimulate interest and entice the customer to make the purchase. This explains the criticality which merchandising holds for any retailer.
Merchandising analytics may not be a new affair for the retail industry but with advancement in the field of analytics and with BI boasting of next-level intelligence, its recently proclaimed status of the ‘new non-negotiable’ in the retail world is quite justified.
Retail industry has long-held the reputation of being an unstructured mess. While it is becoming systematic and better-wired gradually, when it comes to merchandising, the road is still an uphill.
This unstructured setup is in fact, the growth-ground for multiple challenges faced by retailers. The magnitude of impact deepens in the context of growing trend of global expansion.
A quick look at few of the challenges:
- Cluttered, scattered, complex, unstructured, non-standardised and unreliable data due to multitude of geos, languages, formats and processes
- Absence of integrated reporting platform resulting in erroneous and inconsistent reporting and improper process tracking
- Lack of central master data repository resulting in longer TATs for any compliance related correction
- Rise in conflicting interests with portfolio expansions and newer players’ entry
- Increasing limitations in the retail display space and lack of visibility and availability optimization
- Inefficiencies in the distribution network impacting sales growth
- Lack of visibility and measuring parameters pertaining to co-relation between product and brand visibility vis-à-vis revenue generated vis-à-vis customer experience
- Lack of data driven business insights to understand the product, the customer and the market
Analytics Comes to The Rescue
The breeding ground of challenges, i.e. the unorganised characteristic of this domain, is the first place where analytics hits the nail and begins the journey of transformation. Provision of relevant and timely market insights, comprehensive competition intelligence, prescription analysis of pricing optimisation, experimental launch labs etc. then follows. That’s how analytics takes all the challenges mentioned in the previous page, head-on.
To see the tech in action, let’s take the case of one of the trickiest affairs which brands deal with – Assortment Management and Shelf-Space Optimisation – the holy grail of effective merchandising.
It’s trickiest since hitting the sweet spot here is the most daunting task for retailers.
The scenarios can be like: Increasing the variety – it may create confusion among the customers or even increase the sales; identifying the right store for the particular product mix – a wrong move there can impact the sales drastically; evading the narrow product mix risk – there always looms a risk of being overshadowed by a competitor with better inventory mix.
Also, the most important aspect here is, most of these decisions are to be taken by brands months in advance, leaving no scope for last minute change of plans. All in all, a tough path to tread if you plan to base everything on just intuition (and not on insight).
The Art of Right Product-Mix and Best Placement
The analytics application here if seen on a broad level, reveals 3 key steps – Data Collection, Data Assessment and Application & Review. Of course, each of these steps contain multiple other action suites which altogether combines to provide a perfect merchandising.
Looking at each of these steps more closely:
Multiple formats of data with minimal or no structure. Varied and informal templates for data entry. Lack of central data repository causing operational inefficiency.
A standard platform ensuring the mandatory fields for requisite data is formulated after extensive research and demography-specific business process understanding.
The uniform platform allows scientific performance measurement with establishment of clear-cut KPIs. A master data repository allows for shorter TATs and better compliance management.
The ideal bet is a geo and language agnostic platform which allows complete agility for future scale-up otherwise there looms a risk of complexity whenever the scaling-up would be required.
Erroneous, incomplete or inconsistent data. Customer dataata collected through multiple sources and in multiple languages, raises the challenge of standardization. Unstructured processes and gaps therein lead to inaccurate monitoring of operational changes.
The integration and cleansing of the data is followed by its crunching and analysis in an intelligent data assessment engine. Any compliance related issues are also called out at this stage. Image assessment mechanism is also leveraged for integrity assessment of merchandise and for correcting any compliance adherence issue.
Data Discovery – Garnering Insights
In these times of instant feedback and real-time customer reaction capture – both in-store and through social media, delay in strategy implementation review allows for probable miss-outs on requisite amendments.
As part of any deployment, the final insights upon application are reviewed and the reaction data generated is again fed into the analytics engine to assess any probable need of course correction.
Understanding of the correlations & impact and leveraging the insights for better planning & forecasting are also carried out. Product profitability ranking is done based on details such as inventory levels, replenishment status, product lifecycle inputs, market-basket details etc.
In-depth regression analysis with assortment simulator and optimiser then provides insights into store-wise product assortment suggestion along with a suggested timeline for the products (based on seasonality and past-purchase patterns). Optimal assortment in the given shelf-space is also prescribed keeping in mind the store cluster specificity.
Even the training requirement for field agents can be deciphered through the data evaluation and eventual sales review.
The Benefit Brigade
With effective analytics implementation, eventual goal of improving the availability and visibility score is met with actionable planogram strategy, thereby beefing up retailers’ revenue.
At a broader level
Improved visibility of the segment and category along with availability optimisation with information around aisle traffic increase tactics
Complete integration of previously scattered data with majorly improved compliances scores
Smaller TATs for measuring the impact of any implementation, allowing for quick course correction, if required
Improved VM compliance scores owing to scientific and real-time space audit conducts
Identification of revenue opportunities with suggestion around co-merchandising opportunities, if any
Prevention of holding and spoilage costs and provision of higher inventory turnover rates
A localised strategy with a unified view offering a transparent and single version of truth to the management
Total customer centricity through critical business Insights and problem solving based on advanced analytics and data sciences
Models for propensity analysis, risk analysis, fraud analysis, customer segmentation, forecasting using advanced data analytics and predictive analytics
Generate data research and analytics-based business insight reports covering customer, market & ops
- Knowledge about right ratio between trends and staples
- Lessening of visual clutter
- Precise spotting of maximum footfall spots within the store
- Assortment intelligence enabled timely trend-spotting
- Real-time management of assortment owing to information based on competition’s inventory depths or stock-gaps
Merchandising analytics is all about moving beyond the physical product placement stance and using that as a bridge to positively influence customer psychology – eventually resulting in lessened revenue leakage and increased sales.
With a generous dose of benefits, retailers today are leaving no stone unturned in leveraging the new-age analytics and business intelligence for carving their competitive quotient. The rush is now for placing their hands on the most trustworthy partner who provides impeccable services in all these domains – 1. Data assessment and integration 2. Visibility optimisation 3. Availability optimisation.
The one who is able to get the right partner onboard for merchandising analytics can be considered to have hit the jackpot.
If you’re still struggling to find the right match, then you’ve landed at the right place. Let our experts help you up-level your retail game with our offerings such as Retail Audits & Visual Merchandising, as well as Retail Analytics. Just drop us a line for a quick connect.