By Greg Silverman, Nov 09, 2020
The whole is greater than the sum of its parts. This phrase is often thrown around to describe mechanical elements, but what about data? While big data collected from different sources is no doubt useful on its own, only together does it provide a complete picture for businesses to use for strategic decision-making.
This is what unified data aims to achieve. A unified data analytics platform serves as a one-stop-shop for analytics processing and typically replaces a multitude of BI tools, according to Eckerson Group. Still, these solutions often lacked the power to prescribe action from insights, until now.
Unified data as a concept evolved into unified analytics as an action. Unified data analytics uses comprehensive information derived from historical data and forecasting to form recommendations that are used to make faster, better decisions. Let’s explore how businesses use this type of analysis to excel.
While unified analytics is a relatively simple concept to understand, many individuals still struggle to properly track and measure the right metrics. And without focusing on the right marketing measurement, businesses aren’t able to reap the benefits of unifying their data.
Unified analytics integrates internal customer data with external findings derived from data science to help businesses understand consumer behavior and how they react to changes in the market. Organizations must identify the connections between their chosen metrics - typically how a certain segment will react to their decision. For instance, with a unified measurement in mind, marketers are able to ask complex questions such as “If my marketing budget is X, my product price is Y, and the competitor's message is Z, what would our sales be?”
These metrics are found along the customer journey and are the points where consumers begin forming beliefs about your brand. As businesses identify each touchpoint and form a unified picture of their journey, they are able to tailor decisions to enhance it. Steve Jobs summed this concept up nicely when he said, “You’ve got to start with the customer experience and work back toward the technology - not the other way around.”
With unified analytics, the metrics encompass the customer experience and this knowledge helps businesses build accurate attribution models.
Unified marketing analytics brings together previously disjointed silos from big data solutions for a consolidated and meaningful view of the customer journey. Here are five other distinct ways this type of analysis engine helps businesses excel in a competitive environment:
1. Gain a comprehensive understanding of your market
Marketing, finance, and other departments all hold valuable information about the market consumer behavior, but data engineering is much more valuable when analyzed as a whole. Insights derived from data silos are isolated, but unified analytics knits them together for a comprehensive view on how consumers interact with the market, your brand and each other.
2. Target decisions to different segments
Unified analytics not only provides a comprehensive view of the market, it’s also granular enough to segment audiences. Businesses may have a few different consumer segments they want to target, and these groups have different needs and therefore a distinct customer journey. While marketing mix modeling provides a disjointed view of a business’s marketing mix, simulation supports a unified marketing model. With this, businesses are able to structure and quantify data at a precise level to understand how different segments react to change to help drive marketing strategy.
3. Build customer loyalty
Once businesses understand their customer segments, they are able to tailor the buying experience to meet their unique needs. This is especially important when marketing budgets are tight, as unified analytics help businesses identify their top tier segments - those who are likely to purchase their product or service more frequently - and appeal to them to get the most gain from their marketing investments.
With a specific segment to target in mind, businesses are able to structure the data and run scenarios to identify what changes they need to make to entice them to purchase their product over an alternative. When businesses are given a roadmap to enhance the customer journey, they have the opportunity to conquest new consumers and build loyalty among a new, sustainable consumer base.
4. Control costs
Perhaps the best part about unified analytics is that every organization is able to harness its power in-house. As opposed to outsourcing these capabilities to third parties and risk losing proprietary data and waiting months for insights, businesses are able to unite their data and receive recommendations with the help of self-service analytics tools. Organizations control costs by keeping this technology on-premise and make strategic decisions that stretch their budgets further.
5. Achieving faster insights for decision-making
With the help of artificial intelligence, machine learning and other tools that make unified analytics possible, businesses are able to get answers to their questions in hours or minutes rather than weeks or months. The combination of qualitative and quantitative data that unified analytics manipulates helps businesses gain a complete understanding of fluid market behaviors to make decisions in near-time. In an environment where consumer preferences and economic conditions are always changing, this quick turnaround of results is what helps businesses meet their customer’s needs and stay ahead of the competition.
Artificial intelligence has been a hot topic of discussion for the past decade, but is it all it’s hyped up to be? According to Medium, many businesses and people overestimate what AI is capable of. Ultimately, collaborative robots and artificial intelligence have their limits: They cannot actually make things occur.
While this technology undoubtedly has a place in the modern business world, organizations should not rely on it for their strategic decision-making. At it’s best, AI is capable of combing through stacks of data to piece together a framework of something that’s interactive, but it doesn’t have the human capability of turning these insights into strategic action or deep learning.
The modern digital estate for AI needs to be remodeled. Just as data analytics has evolved from describing information to predictive analytics and prescribing a path to future performance, AI must be used as a tool to build off. While it’s used alongside automation to help spot trends and data and provide useful insights in minutes, business users are also an integral part of the process. It’s up to them to act upon these recommendations and make the decisions to reach their desired outcome.
Even with artificial intelligence, the decision-making process will never be fully automated. The new digital estate utilizes unified analytics to derive a cohesive outcome and uses knowledge about human instinct to help drive business decisions. The Concentric model embraces this change by utilizing unified analytics at its core to effectively break down data silos and foster internal collaboration to help businesses understand their market. To learn more, contact us today.