Using Cloud Data Analytics to Drive Engagement

The decisions a business makes to help drive revenue and increase customer loyalty are only as good as the available data being referenced. Given the state of consumer demands and the changing ways they prefer to interact with brands, now is a crucial time for businesses to take stock of their cloud data analytics strategies. If data in the cloud isn’t being effectively integrated into the enterprise for analysis and insights, then meaningful business decisions cannot be made accurately. 

Customers are now taking their buying experiences more seriously than ever before. Nearly three-quarters of US consumers rank their experience dealing with a business as being important to their buying decisions. A large majority (86%) say they’d even pay more if it meant getting a better customer experience (CX) out of it. 

For businesses, this means that learning as much as possible about customers and getting their buying experience right is the #1 priority. Combining the power of modern-day analytics with the flexibility offered by the cloud can help businesses generate the real-time insights needed to grow and develop CX. Understanding a customer through data requires a thoughtful approach to cloud data analytics and how to effectively harness data for maximum output.  

Cloud Data Analytics, Explained

The phrase “cloud data analytics” can mean many things to many different businesses, but broadly speaking, it’s all about using data to make smarter decisions to retain customers and win new ones. In some cases, it may refer to the way customer information is gathered to profile a new target sector. In other cases, it may refer to the way a business pinpoints where a customer is on their customer lifecycle and how they’ve engaged with a brand. 

However, the goal of cloud data analytics is to paint a holistic image of how to best reach the audiences that are needed to push the business forward. The use and application of these analytics have surged within the past few years. The rise of social media in the past decade has created groundswells of data on consumer feedback, with sites like Facebook and Instagram providing spaces for customers to describe their experiences with brands. Similarly, aggregator sites like G2 Crowd and Quora allow for reviews and direct questions to be asked to and about companies. 

Businesses can leverage this data for their analytics in several ways, but perhaps the most important gain is using those insights to improve marketing and advertising campaigns. Consumers want personalization more than ever when interacting with businesses, and the insights generated from existing customer data can help make that personalization a reality.  

Understanding a consumer’s buying history and behavior can better help marketers choose the messaging that will resonate best with that customer and hopefully retain them. The need for personalization here cannot be overstated – competitive businesses must know their customers.  

I’m sure that we’ve all gotten offers from companies after visiting their website or buying a product. If a consumer buys a set of sheets online from a major retailer, the next email they receive should probably be for a sale on comforters, not refrigerators. Too many irrelevant offers, and your customers will begin to view little value in your communications and unsubscribe, meaning losing opportunities to attain leads. 

Cloud data analytics can also help organizations meet consumers where they are and on the channels they prefer. As mentioned, the near-ubiquitous use of social media in recent years has ushered in a new wave of opportunities for marketers to meet consumers on these platforms. Leveraging data in the cloud for analytics can help organizations build up an effective social media strategy, one that offers insights into the way customers are using these platforms. Given the nature of today’s interconnected world, social media represents a huge chance for marketers to meet their customers on familiar ground. 

Moving Up to the Cloud 

Before a cloud data analytics strategy can get off the ground, the data being used needs to be clean, secure and easily accessible in infrastructure that can scale with today’s data growth. Traditional storage setups like on-premises data warehouses may have a role in today’s enterprise tech stack, but they can’t keep pace with the explosive growth of data from marketing applications. This means businesses still using legacy data centers should consider a move to the cloud for data storage.  

By leveraging a cloud storage model, users can dynamically scale their warehouses according to their business needs. Cloud data warehouses also ensure that the datasets stored inside of them are structured, compliant with regulatory standards, accurate, and accessible to any team that needs access. Furthermore, cloud-based warehouse architectures are significantly speedier than their on-premises counterparts, so you gain access to customer data quickly and efficiently – allowing you to meet customer demands as they happen. 

Perhaps most important, by leveraging the elasticity of the cloud, you have a more cost-effective way to handle spikes in business activity. Seasonality, market changes, and changes in current events can be addressed immediately, instead of wasting time waiting on infrastructure provisioning to accommodate the change in demand. This is particularly true when that demand is unforeseen, like we witnessed during the early days of the pandemic. 

Putting It All to Use

Now that the goals of a customer data analytics strategy have been identified and the data has been moved to the cloud, a business can then begin using the data for analysis. Here are some key ways to leverage data to connect with customers: 

Find Areas of Opportunity

It’s important to know your customers as intimately as possible, including their likes, dislikes and needs. The more you know about your customer base, the better you can pinpoint areas of opportunity within your company. The more opportunities you find, the higher chance you have of meeting those needs and making a sale. 

Keep an Eye on Customer Sentiment

There are more channels than ever for customers to leave product reviews, ask questions, and engage in conversations surrounding your products. A large portion of those channels will not be within your control, but by leveraging the data from these places, you can not only respond to customers where they are, but over time gain a bird’s eye view of customer sentiment as well – both good and bad. The trends you uncover will help your product teams to address areas of improvement and help your marketing teams to zero in on clear value propositions. 

Get Early Warning Signs Before They Happen

One of the most important benefits of customer data analytics is being able to see early warning signs before shifts in behavior happen. Whether that means a dip in sales or a shift in sentiment from customers, getting ahead of changes can give you more time to react and address issues before they impact your goals. Being able to take preemptive action will allow you to do some damage control before it becomes an irreversible issue for your company. Effectively leveraging cloud data analytics can be a major influence on how businesses drive CX and secure revenue. Access to clean data that can be easily shared can unlock new insights on customers and how to keep them coming back for more. 

For more information on how the Actian Data Platform can help you better connect your cloud data for real-time analytics, check out our blog. 

About Traci Curran

Traci Curran serves as Director of Product Marketing at Actian focused on the Actian Data Platform. With more than 20 years of experience in technology marketing, Traci has previously held senior marketing roles at CloudBolt Software, Racemi (acquired by DXC Corporation), as well as some of the world’s most innovative startups. Traci is passionate about helping customers understand how they can accelerate innovation and gain competitive advantage by leveraging digital transformation and cloud technologies.