The retail industry is always at the forefront of transformation and is currently undergoing a paradigm shift. As data-driven insights replaced intuition-based thinking, retail analytics play a key role in driving merchandising decisions in the retail industry. Customers now have many avenues to interact with retailers, be it in-store, online or mobile apps. So, the experience needs to be consistent in order to have an impact on sales for the retailers.
Merchandising analytics plays a vital role for every retailer to enhance their revenue and RoI. By implementing retail analytics, optimizing inventory management strategies, pricing decisions, brand management, and the customer behavior analysis retailers can drive their merchandising decisions and enhance sales for their organizations.
What do retailers need to do to enhance customer satisfaction?
Most retailers now embrace advanced technology like machine learning, and Gen AI to enhance the experience, improve sales and RoI. But the retail teams need to rethink the following for enhanced customer satisfaction.
- Rethink data sources, including in-store shopping videos, sensor data, and correlating data across channels for a deeper understanding of customer behavior.
- Optimizing shelves and inventory by not just estimating the sales but relating to consumer behavior from varied sources.
- Estimating the market scenarios and competitors’ moves constantly to stay ahead of the curve and agile.
- Online is no longer a mere marketing channel and considered the critical one in the robust omni-channel strategy.
- As product life cycles tend to be shorter these days, retailers need to embrace predictive capabilities for category management and product patterns.
To consider the above transformation for retailers, merchandising analytics play a vital role in the overall strategy and execution. Let us look at how merchandising analytics will impact key decisions for retailers.
How do retail analytics help key data-driven decisions
Understand customer journeys through their life cycle
In this new age omni-channel era, retailers need to understand every interaction from their prospective buyer, existing customer while attracting new buyers. It is getting tough to know where the customer will abandon the buying pattern and shift the quest to other retailers or products. An extremely satisfied customer may also shift given the experience that he could sense from a niche retailer or a leading brand. It is not enough to have an attractive store layout, online experience, and social media presence.
Retailers need to leverage merchandising analytics to understand every footprint of the customer, and consistently fix the gaps with in-depth data analysis. Retail analytics will help you understand the navigation of customers from online to in-store pickups and vice versa. Retailers need to leverage data from every touchpoint in the customer’s journey so that they can help with a cohesive experience across channels and delight them with the utmost satisfaction scores.
Inventory management
Maintaining optimal inventory is another challenge for most retailers. At times, it may cost billions if the retailers do not have adequate inventory to meet the demand or if they are overstocked.
Predictive analytics will help the retailers in forecasting the sales as well as demand by sensing the demography data, market conditions and analyzing the consumer behavior. Every store location may not have to manage the same inventory levels depending on varied factors. Thus, it is very important to leverage retail analysis to deep-dive the data and predict the sales to the granular level.
Pricing strategies
The retail industry is very competitive and price-sensitive. As retailers embrace omni-channel strategy, they have to shift to dynamic pricing models. Lightning deals on online sales platforms have become competitive to attract customers. Even the in-store prices have to be dynamic to reduce the shelf life of different products. Gone are the days when retailers used to share monthly newsletters with upcoming offers and attractive sales brochures. Customers now anticipate a surprise deal at the checkout too.
Robust advanced analytics have to be implemented by retailers to deal with these dynamic pricing strategies. Even analytics platforms like Azure machine learning now offer simple solutions to meet the ever changing needs for retailers.
Personalization
More than 80% of customers feel positive about a brand after reading customized content. Shoppers will be more excited to buy from a retailer who has understood their needs effectively. Fashion and beauty retailers often perform customer segmentation and targeting to offer personalized products to every customer category.
Predictive analytics from customer behavior and their lifetime value will help retailers to offer personalized marketing to the utmost customer satisfaction.
Brand management
We may not solve the puzzle with retail analytics if we leave marketing. The most important thing today is to understand how a brand campaign is performing. Do we have any white space left to attract customers to our best selling product? How do we improve visibility for our online marketing efforts? A lot of questions like these can be answered by leveraging simple analytics solutions.
Placing an ad based on the visitor traffic and engagement will be a no brainer for marketing teams if they drive their decisions with data.
Top benefits of adopting Retail Analytics
Accurate forecasts for strategic decisions
We now have advanced solutions like Azure Machine Learning to analyze large volumes of data and accurately forecast demand and sales volumes. We used to see no stock signs during the busy holiday season in the past. Now that retailers back their every decision with data, we are able to easily shop through the busiest Thanksgiving holiday season too.
Operational efficiency
As per Deloitte, hybrid retail will continue to evolve through the next few years. So is the focus on operational efficiency. Retail analytics play a vital role in cost optimization, effective usage of resources and better online and physical store management.
Customer delight and satisfaction
More than 55% of customers will mostly be a repeat buyer if they tend to have personalized experience with a retailer. Retail analytics offer a complete inside view about a customer, their buying patterns, life time events, preferences and the choice of services. This will help retailers to easily offer them personalization to the utmost satisfaction.
Are you looking to implement a robust analytics solution but that is simple to scale? Our experts are here to offer a quick consultation to access your technology landscape. Give us a few minutes and we will be able to scale your analytics capabilities.
