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Implementing Cloud Computing and Data Analytics Solutions in a Retail Company (with Case Studies)

Big Data | September 02, 2020

Implementing Cloud Computing and Data Analytics Solutions in a Retail Company (with Case Studies)

This time last year, no one, not even a machine could’ve predicted correctly, how 2020 would’ve turned out. A global pandemic of this scale is a black swan event, the likes of which happen once a century. And after nine years of steady growth, this pandemic hit the retail and supply chain industry even harder.

However, not all companies in retail were impacted the same way. Businesses with an online presence, in particular, were able to mitigate losses as shoppers adopted eCommerce over brick-and-mortar shops whilst over half the world went into lockdown. And the number of online shoppers skyrocketed.

To put this growth into perspective, online sales had been steadily growing at a rate of about 1 percent per year. And in March 2020, 18 percent of all sales were online. But in June 2020, 28 percent of all sales were online. An increase of a full 10 percent! In other words, we saw ten years of growth in the span of just eight weeks.

The overall eCommerce growth is expected to be around 18 percent for 2020 and while some of these sales will decrease a little as supply chains and brick-and-mortar shops reopen, the majority of these new online shoppers are expected to say.

What does this mean for retail businesses all over the world?

The clock has been moved ahead by about 5-7 years and digital transformations that you were planning for the next few years should be done right now.


How Retail and Supply Chain Businesses Can Keep Up with The Times

The reason some businesses are able to make decisions confidently in these critically uncertain times is that they are using company history for data analytics but filtering it to take into consideration any outliers. We’ll talk about data analytics in detail in a minute but in a nutshell, what this means is that some companies in the industry have more answers to current problems.

Fortunately, a lot of these answers apply to your company as well.

For instance, with sudden (and in many cases, exponential) increase in online traffic, most companies are making a shift to the cloud and serverless computing. The main reasons behind this shift include:

1. Cost

Cloud computing will be, undoubtedly, more affordable for the vast majority of companies because the inherent costs of on-premises IT solutions do not carry over to a cloud platform. For instance, businesses no longer need to pay for hardware costs, extra IT personnel, third-party software, and more. Additional cost-savings come from the pay-as-you-go pricing schemes that means businesses are billed only for the resources they use. So if Wednesdays and Thursdays are particularly slow, then you’ll be billed less.

Introductory discounts and offers further drive down the price.

Related: The Long Term Cost Benefits of Cloud Migration


2. Stability and Scalability

High loads that usually come with days like Christmas and Black Friday often lead to downtime which in turn leads to losses. Even a single laggy page can increase cart abandonment. And these sort of loads will be a lot more common with so many more people shopping online these days.

Traditional on-premises systems may not be built to handle this but the thousands of computers that are available on-demand certainly are. Additionally, cloud-based infrastructures are built to be resilient with enough capacity to handle high loads without any affecting site performance.


3. Modern infrastructures

Cloud computing uses some of the latest technologies in application development, data analytics, and more. These protocols are designed to be compatible with the modern design philosophies like agile development and DevOps, increasing your team’s productivity and reducing costs.

Another benefit of these modern infrastructure are managed services. Cloud service providers like Google Cloud Platform provide hundreds of services that help you break free from licensing of third-party services.

Here’s a case study of a multi-billion dollar supermarket chain that saw 10X performance improvements by leveraging a modern cloud infrastructure.


How Retail Companies Are Implementing Cloud Computing Solutions

Cloud computing can be leveraged in literally hundreds of ways to create competitive advantages and get ahead in this race to be digital.

That said, if you’re a legacy business with no experience with cloud computing, you’ll probably want to avoid experimenting in the middle of a pandemic. Instead, you can take inspiration from the following proven cloud computing implementations by retail businesses and innovate with time.

1. Cloud-based Storefronts

If you’re a business that can sell online (even locally) then a fast, reliable, and scalable eCommerce platform is a must. There are quite a few vendors that provide hosting service providers that you can use to host your store website but if you’d like access to a (much larger) ecosystem that will act as an “all-in-one” solution, then a cloud vendor is the obvious choice.

Another argument for moving to the cloud is the level of freedom developers have over their product. With technologies like Kubernetes (microservices), retail businesses can offer better customer experience thanks to faster updates, fewer bugs (automated testing and feedback loops), and better speeds. Your development team will thank you for the other cloud-based tools (hundreds of them) that aid application development.

Here’s a case study of Lush, a cosmetics brand with over 930 stores in 49 countries that managed to migrate its global e-commerce site to the cloud in just 22 days.

Businesses with existing storefronts can also migrate their website to the cloud to enjoy better pricing, more options, and stability.


2. Enriching customer experience with cloud-based applications

Cloud vendors like Google have developed their cloud computing services to be customer-centric. Many of their services were designed specifically for retail businesses like Looker which empowers retailers with business intelligence, data applications, and embedded analytics.

Furthermore, companies can use AI-powered tools like Vision API and Recommendations AI to create innovative and engaging software that enrich the customer experience.

IKEA uses GCP’s Vision API to make buying home decor products easier, faster, and more fun

The retail industry depends on customer experience more than any other industry and so there is a constant battle between businesses to provide the best customer experience. This is especially true for businesses who are often unable to compete on prices.


3. Transforming productivity both online and offline

For retail businesses with brick-and-mortar shops, it’s important for the online and digital benefits to translate over the offline world and directly increase revenue. Cloud computing does this by reducing costs and increasing profits.

For instance, many of the software that comes bundled with Google Cloud Platform can be used by employees and increase productivity. Employees (both developers and administrators) can collaborate faster, smarter, and more effectively with tools like GSuite, Chrome Enterprise, and Android.

GANT, a retail giant operating in hundreds of locations spread was able to reclaim 150,000 hours of employee productivity a year, reduce travel costs by 20 percent, improve order management, and delivery times - all thanks to the cloud.

Read the case study.


4. Managing Inventory and Forecasting Demand

If you’ve already been using some inventory management tool, you likely understand the importance of accurate forecasts. However, the cloud is different from most inventory management software in the market in one powerful way - cloud vendors have access to some of the most advanced artificial intelligence (AI) out there.

What this means is that the benefits of the billions of dollars that companies like Google and Amazon have invested in developing their AI and machine learning (ML) algorithms can be used by retailers to avoid stockouts and excess inventory. Google offers numerous supporting services and technical expertise to help companies infuse AI into their day-to-day tasks, making them more accurate and reliable.

Here's a retail case study about California Design Den who saw a 50% reduction in inventory carryover by using AI inventory management.


Here’s a list of even more cloud computing implementations for retail businesses:

  • Build modern retail-specific applications (PoS, delivery tracking, reviews, notifications, etc.)
  • Use hybrid and multi-cloud for reliability testing before product launches.
  • Warehouse modernization and automation
  • Workplace automation
  • AI-based customer service (conversational tech)
  • Targeted digital marketing

Predictive Analysis for Accurate Predictions and Q3 & Q4 Planning

A steady growth period of nine years has allowed retail companies to optimize their product life cycles and operations through years of data. The insights derived from this data has also helped the retail industry scale operations in everything from supply chain and logistics to inventory and staffing.

But there are two kinds of businesses in the retail industry: ones that are already using predictive analysis and the ones that aren’t.


Harnessing Existing Data Post COVID-19

Most of the data analytics companies conduct time series models that allow them to use past trends and historical data to create assumptions about future trends. Thanks to advanced data analytics models from cloud vendors like Google, these assumptions can be extremely accurate. However, the same data cannot be used going forward because of this pandemic. But your existing data isn’t useless.

COVID-19 has thrown off everything. The models predict a large spike in sales in August similar to last year but we know the sales will be a lot less. COVID-19 is an outlier (a very severe one at that) and to be able to continue making accurate predictions, your analytics model must be able to take this outlier into consideration.

This is where advanced AI data analytics comes into play.

By filtering historical data (last year’s, for instance) with COVID-19 numbers in an advanced AI model, retail businesses can predict the gradual return and reopening of shops and plan their inventory accordingly. And therefore, leverage their existing data for predicting Q3 and Q4 and making overall better plans.

This type of analysis steps into the world of data science that although is more complicated, can be far more rewarding.


Setting Up Predictive Analytics for Q3 and Q4

Being data-driven is highly underrated, even in 2020 when almost every major retailer is leveraging big data (collecting and analyzing massive sums of data). The reason is that most small-medium retailers do not have a roadmap that allows them to set up proper data analytics and thus predictive analysis.

But now is the time. And to help you, you can use the following three steps to get started:


Step 1: Identify pain points

Through a comprehensive audit, retailers can and must identify the pain points of their businesses. Common pain points for retailers include marketing, inventory management, and customer service. The premise behind identifying business problems early on is to create targeted solutions. The bigger the problem, the bigger the gains upon solving it.


Step 2: Start collecting data (external and internal)

Oftentimes, businesses will only collect key performance indicators (KPI) data. However, in our experience, that can give you limited insights as business executives only see good or bad performance without any data to explain that performance. For this reason, collecting a lot of data is necessary.

And since according to a Harvard Business Review, 85% of business performance is influenced by external factors, businesses need to collect as much outside data as they can.


Step 3: Use automation

With the cloud, nearly all of a business’ data mining can be automated. Not only that, but AI data analytics also allows retailers to sort and analyze the data all on its own. AI data analysis requires knowledge of data science but by using machine learning algorithms, retailers don't have to constantly monitor data analytics as the results become accurate over time.


Cloud computing is a big new world with limitless possibilities for retailers. Unfortunately, this is one of the reasons why many have avoided it for so long - it’s easy to get overwhelmed. Retailers, especially, legacy businesses can and should take the help of experts to avoid costly mistakes. D3V Tech has been helping retailers create and implement cloud roadmaps, helping retailers with everything from cloud migration and app development to data science and analytics. Schedule a free consultation with a cloud-certified engineer today to get started.

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