Customers interact with their favourite brands through many channels these days. They search for products online, ask for recommendations from their friends, refer to brand’s social media platforms, and then take a decision to buy or not. With the surge in the choices available to them, they are more vocal in demanding awesome retail experiences and more prudent in making purchasing decisions.
Due to this shift in customer behavior and buying patterns, retail businesses need to invest in transforming their operations, technologies, and workforce, and deliver a consistent personalized customer experience across all channels.
In an effort to understand retail challenges and the ways to mitigate them, MediaAgility partnered with Google Cloud and facilitated a roundtable discussion – ‘Intelligence in Retail: An Innovation Forum’ at Google’s NYC office. The roundtable provided for a candid setting for select retail leaders to come together as peers and table the challenges faced by retail organizations nationwide.
The D Day – candid conversations to exchange challenges and insights
The roundtable was attended by a select group of top execs from leading retail companies in NYC along with a handful of technology evangelists from Google Cloud and MediaAgility.
Top three challenges tabled at the roundtable :
- Data & Infrastructure – challenges in adopting advanced technology infrastructure to tackle the massive explosion of data, like:
- Cost and operational burdens in analyzing customer data
- Siloed data accessed with disparate tools
- Difficulty in scaling and maintaining the legacy infrastructure
- Lack of real-time view of inventory and sales across channels
- Customers – challenges in redefining customer experiences and engagement, like:
- Richer and balanced experiences enabling the customers to explore products and categories without actively pushing them
- Analysis of customer’s activities and behaviors across all brand channels to provide personalized consumer experiences
- Operations – challenges in shortening the response time to customers and cost of operations, increasing efficiency and output, like:
- Same day delivery of retail e-commerce order and inventory management
- Re-evaluation of operations and tools to scale growth
- Collaboration between departments, store-front and backend staff, and IT costs and investments
Retail heads in attendance felt the need for more quality insights into their organizational data, customer behavior, and operations. They realized the value of getting hands-on insights from data and how that could transform every aspect of their business ranging from marketing analytics to workforce transformation to app development and others, yet they were unsure on how to adopt Analytics and ML to arrive at these insights from data.
They wanted to explore the technology, cost, resource, security, and time requirements to adopt and run a mature Analytics and ML machinery for their business. Most participants were on a look-out for a solution to actionize their data, hence allowing them to focus more on their core business.
To paint a picture of the endless opportunities offered by Analytics and ML, MediaAgility shared a more recent example of a multinational lifestyle retail brand. The Cloud Architects at MediaAgility helped this brand to build a real-time store dashboard with predictive analytics in place. The solution ingests real-time sales and store traffic, conversions, weather forecasts, holiday spikes, and historical data from the brand’s hundreds of stores into the algorithm, and predicts and provides real-time insights into their store performance. As a result, the brand has optimized staff availability, inventory and gained business-critical insights ahead of the holiday season.
Further, the participating Google Cloud engineers established how Google Cloud’s state-of-the-art architecture and products secure enterprise data, scale and enable real-time analytics.
Live in action: Insights from live data and streaming analytics
MediaAgility showcased a demo of its indigenous solution – ‘Real-time Store Traffic Segmentation & Streaming Analytics Using Facial Detection’. The real-time analytics demo simulated the store’s entrance. It captured the demographics of the shoppers and used home-built Machine Learning models to get insights from the real-time visual data. The insights were analysed on a live dashboard that leverages GCP to pool in data from potentially infinite number of locations simultaneously.
Intelligence in data opens up many avenues for retail businesses
Retailers are now at an advantage like never before because they can derive intelligence from data. Retailers can be closer to what the customers say and need, they can leave longer-lasting impressions on the customers with personalized experiences, and can have efficient and automated operational processes.
MediaAgility recommends retail companies to prioritize
- Meeting peak demands with elastic resources
- Embracing modern technology stacks
- Enriching your customers’ experience
- Adapting to changing market conditions more rapidly
- Incorporating advanced analytics in all facets
- Planning for connectivity with broader systems
- Building for an online and in-store experience
As stakeholders in this industry, the roundtable attendees could see and experience the possibilities of insights from data through Analytics and ML. Interested to discuss ideas around Data Analytics for retail? Write to us at firstname.lastname@example.org