5 Ways Retailers Can Meet Post-Pandemic Shopping Expectations

SADA Says | Cloud Computing Blog

By SADA Says | Cloud Computing Blog

COVID-19 changed how Americans shop, and the changes are likely permanent. Even before COVID-19, consumers were shifting away from brick-and-mortar stores and towards eCommerce, but the pandemic put this trend on overdrive; IBM recently estimated that COVID-19 accelerated it by about five years. A recent survey by TOP Data supports this assertion, revealing that nearly three-quarters of consumers have been shopping online more frequently since the pandemic began, and 88% intend to keep shopping online even if a vaccine or cure is found.

To compete in this new environment, retailers must rapidly build out not only robust digital channels but also the omnichannel fulfillment options that consumers have embraced during the pandemic, such as buy online and pickup in store (BOPIS). Inventory management and world-class customer service are also more important than ever. The items that consumers are buying have changed as drastically as how they’re shopping for them (think a lot less clothing and a lot more household items), and online shopping means that competitors are only a click away.

Here are 5 ways retailers can use Google Cloud to restructure, digitally transform, and meet customers’ new, post-pandemic shopping expectations.

1. Use Location-Based Data to Deliver Customer-Centric Experiences

Far more than a driving directions app, Google Maps Platform allows retailers to leverage location-based data and insights and deliver shopping experiences that are more personalized and customer-centric than ever before. Here are just a few ideas:

  • Keep customers updated on operating hours, temporary closures, and special shopping times for seniors and front-line workers by displaying this data in the Maps app.
  • Provide customers with real-time tracking and accurate delivery times, including estimated delivery times for each product prior to a customer adding it to their cart.
  • Streamline the BOPIS process with faster and more accurate home address entry during checkout, a map displaying the customer’s closest pick-up location, and turn-by-turn directions to the pickup location, complete with real-time traffic information.
  • Display critical customer and order data on an easy-to-read map for a visual representation of which locations are flourishing or struggling in a particular region.

2. Enable & Optimize Front-Line and Remote Workforces

Many retailers, including grocers, home improvement stores, and mass merchandisers, are on hiring binges to keep up with skyrocketing demand. Google Workspace helps retailers enhance productivity, enable collaboration, and drive operational improvement among both front-line and remote workforces.

Retailers can use Google Drive as a centralized location to store marketing, product, and inventory information, and automatically push updates out to their website, mobile app, in-store digital signage, and handheld devices used by in-store staff. Employees can share documents, images, and other digital assets easily, securely, and with the assurance that everyone is always accessing the most up-to-date version. 

Using Docs, Sheets, and Slides, teams can collaborate on documents, presentations, and spreadsheets in real-time, as well as manage team activities with a shared task list in Google Sheets, a team calendar in Google Calendar, or both.

In addition to keeping remote workers connected, Google Meet’s live video conferencing capabilities can be harnessed to help front-line staff deliver superior customer service. For example, Schnucks, a family-owned grocery chain in the Midwest, uses Google Meet as both a dispatching tool and a help desk for its in-store staff.

3. Use Smart Analytics to Make Data-Driven Decisions

By migrating to BigQuery, Google’s modern, serverless data warehouse, retailers can derive maximum insights from their data while enjoying extraordinary speed, scalability, and flexibility and without increasing their administrative overhead. Analysts can focus on distilling insights from petabyte-sized datasets without concern for provisioning or configuration — even if that data is stored on AWS. BigQuery Omni, now available in alpha, allows users to directly and securely access data in AWS databases without the need to move it, copy it, or incur egress fees. 

BigQuery seamlessly integrates with all other GCP tools, including Looker, which offers pre-built, retail-specific data models and analytics packages, called “Blocks,” that allow retailers to combine multiple datasets across the organization and get a big-picture view of in-store operations, product margins, and other operational data. Looker also integrates with Google Cloud for Marketing solutions, allowing retailers to combine and analyze real-time data from Google Ads, YouTube, and Google Analytics and make immediate changes to existing digital marketing campaigns.

Using a combination of BigQuery and Google Analytics 360, retailers can perform granular and complex querying of unsampled information, including clickstream and web metrics data, and use it to adjust user recommendations and SEO. They can also combine Analytics 360 data with other first-party data, such as point-of-sale information housed in BigQuery, to gain insight into cart conversion rates, coupon code usage, and other factors that impact the sales funnel.

4. Use AI/ML to Improve Inventory Management & Increase Conversions

Google Cloud democratizes AI and ML with fully managed, user-friendly tools designed for developers, analysts, and other users who don’t have a background in data science. BigQuery ML, for example, allows users to build and deploy advanced ML models using only basic SQL.

With supply chains still under stress, retailers must be able to accurately estimate customer demand to avoid stockouts or excess inventory. Using Google Cloud’s AI/ML solutions, such as BigQuery ML, analysts can easily develop custom models using their own data points to forecast product demand and gain a better understanding of how their merchandise is moving across channels. These models can be fine-tuned on a location-by-location basis using Google’s extensive library of public datasets, including weather information, traffic data, COVID-19 tracking, and more.

Google’s AI Building Blocks allow developers to integrate sight, language, conversation, and structured data into their applications and deliver highly personalized customer experience. For example, developers can utilize Vision Product Search and Recommendations AI to improve product recommendations for both first-time visitors and loyal customers.

5. Build a Smart Contact Center 

As digital shopping spiked, many retailers’ customer contact centers became overwhelmed. Google’s Rapid Response Virtual Agent enables retailers to deploy chatbots within two weeks. The virtual agents, which can work over chat, voice, and social channels, converse naturally with customers and answer simple inquiries, such as questions about store hours, order status, and pickup options, allowing human customer service agents to focus on complex cases and minimizing customer wait times.

Retailers who want even more functionality and operational efficiency can deploy Google Cloud’s Contact Center AI, which enables virtual agent chatbots to not only converse with customers but also assist human agents with complex inquiries. When a virtual agent can’t solve a customer problem on its own, it seamlessly connects the customer to a human agent, but it also goes a step further. Using natural language recognition, Contact Center AI determines customer intent and provides real-time, step-by-step assistance to human agents.

Additionally, Contact Center AI identifies call drivers and sentiment so that contact center managers can better understand customer interactions and improve outcomes. To learn more about generating value with AI, check out SADA’s Next OnAir post-session recap videos in our insights section.


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