02nd Dec, 2019
Denave, Team, Designation
Retail – a domain which can easily be regarded as one of the most unstructured yet massive industry sector, is sitting on the fence of an unparallel revolution. A revolution which has transformed not just the industrial realm but the whole world on one level.
We are talking about data revolution.
Retail churns out an unprecedented amount of data every day, every second – be it the sales data, footfall figures, online product views etc. – the sector just never stops streaming data. This makes it the most ideal ground for analytics application since precision in analytics depends upon the quantity as well as the quality of data.
Retail analytics is picking up pace globally and UK & APAC markets are one of the frontrunners in leveraging tech-integration in retail.
However, it is the quality of data which is always a matter of concern for retailers globally.
The challenge of quality database owing to various reasons like non-uniform platform preference, multiple format followership, language disparities etc. then becomes the hatch ground for multiple other macro and micro concerns such as:
- Cluttered, scattered, complex, unstructured, non-standardised and unreliable data
- Absence of integrated reporting platform resulting in erroneous and inconsistent reporting and improper process tracking
- 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
- Lack of central master data repository resulting in longer TATs for any compliance related correctio
- Increasing limitations in the retail display space and lack of visibility and availability optimization
In short, inability to make sense of the data that is being generated or extract actionable insights from the same translates into disconnected journeys, delayed decisions, ill-managed distribution network and overall, a sub-par performance.
If you’re experiencing any of these up to any varying extent then either you immediately need a retail analytics solution or if you’ve got one already, then you may need to assess your vendor and see if you’re caught in a ‘poor’ partner relationship.
With an expert retail analytics partner, you get the resolution to all these challenges (and much more). But then, in a world where it’s a crazy crowd of companies claiming to be the next-gen database expert and analytics ninjas, ensuring to have your right-fit partner onboard can be a daunting task.
After all, a wrong partnership can cost you consumers because in retail the scope for errors is minimal and a seamless & relevant consumer experience overpowers brand loyalty anytime.
Here, we have parametrised the outcomes in the form of a quick 4-point checklist, which you can use for assessing your current retail analytics solution or leverage as a guide for finding a perfect service provider:
- Beyond the claims of ‘good’ quality data sieving and management, you need an intelligent end-to-end data management engine which cleans and simplifies data, standardizes it regardless of language, format & process and identifies gaps in the process of data generation & data collection.
- Also, look at the data assessment engine which not just crunches your data based on predefined theoretical metrics but also leverages new-gen tech like image assessment for a more real-time compliance adherence.
- Apart from geo, language and process agnosticism, it is always wise to place your bets on a solution which allows complete agility for future scale-up otherwise there looms a risk of complexity whenever scaling-up would be required.
- A consistent and seamless omnichannel experience is the key to get the customer coming again and again. Therefore, even when selecting a retail analytics solution, you need to look for a partner whose services and support doesn’t become narrowed once the sale has occurred.
- Integration of technologies like machine learning in the retail analytics solution to get faster, more accurate analysis and trend insights, will ensure that you remain ahead of your competitor in identifying growth drivers and gauging and sustaining consumer attention.
- Quicker analysis and real-time actionable inputs mean shorter TATs and better compliance management, thus – happy and consistent consumers (and therefore, a steady stream of revenue for you).
- Look for a uniform database platform, which in turn allows scientific performance measurement with establishment of clear-cut KPIs.
- A good solution will be providing a comprehensive yet single-window view on sales vs stock vs compliance, availability and visibility conformations and a holistic view of market, customer, competition & operations
- Contrary to its name, this one is hands-down the most critical aspect because when you’re spending money, you don’t want to remain tangled in the nitty-gritties of complex processes or get some fancy and complicated analysis etc.
- Hallmark of a good solution would be its ease of use even by a non-technical user because there’s no point of having a retail analytics solution where your decisions are still slowed down because of IT dependence for dashboard management and report generation.
- Another important feature to check is if the solution goes beyond analysis presentation and shares automated recommendation to further accelerate your decisions.
- An interactive platform with non-jargonised visualisations and business insights which is accommodating to your existing processes is always a better investment than a hi-tech but complex solution.
Retail 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.
The famous Peter Drucker quote – ‘If you can’t measure it, you can’t manage it’, fits aptly with the retail industry today. And thus, integration of analytics is no more a choice but has become a mandate for retailers.