Forrester noted in its 2016 report that as customers grow increasingly empowered by new technologies and have greater access to rich information resources, they now need brands to respond quicker, better, and more efficiently to stay relevant.
Ask any marketer today what the latest “must-have” in their marketing funnel is, and you will likely find data analytics as one of the top demands in response to such pressing customer needs. While brands are getting better at collecting and collating data sources, most in fact are still trying to play catch-up with understanding the data and providing useful, actionable insights for the sales organization.
This trend is hardly something new. Similar to buzzwords like “content marketing” and “account-based marketing,” using data, understanding big data, and applying it to business decisions have been on the to-do list of CIOs and CMOs alike for as long as we can recall. (To be fair, the concept of big data may date back as early as the 1940s, so it has been a while.)
Data analytics today is being used across functions to address varying levels of personalization in a multichannel market. Customer experience (CX) teams may use this to address previously logged issues or experiences and provide better recommendations when engaging the customer. Digital experience teams may use online engagement statistics to drive their next UX updates and map digital pathways across online channels and assets.
Sales teams tap on data such as demographics, spend history, and likes to develop a look-a-like of their best customers. Marketing continues to strive for better marketing return on investment, and more importantly, clear attribution to the business’ bottom line.
Data for me, data for you
So it looks like using data to make informed decisions is no longer a privilege limited to big businesses. We know for a fact that knowing where to look for the right information is the first step of getting on track to delivering data-driven success. Customers know that too, and as knowledge keepers of customer data within an organization, sales and marketing may hold the key to pulling together the right technologies, people, and processes to truly make data analytics work.
Ideally, sales and marketing each own clearly-delineated sources of customer data and put these into a comprehensive database, supported by sales and marketing automation tools that can help keep the leads pipeline healthy and revenue projections on target.
“Data preparation accounts for 80% of the work of data scientists.”
In reality, data siloes—amongst other challenges—remain the bane of organizations trying to move ahead in their pursuit of powerful analytical insights.
According to a survey of data scientists, data preparation alone accounts for 80% of the work they do, plus 60% of time spent on cleaning and organizing that data. Harvard Business Review further cements these findings, listing out the multiple reasons of how isolated data pools can lead to the impending failures of data initiatives. All these statistics and findings make the hopes of tapping into the immense potential of data look bleak. However, in more recent times, finding a viable combination of software applications may just be the simple answer to a complex question.
Working backward for the right decision
Your data can be a gold mine if you’re able to put it to work at every level of your organization. If you don’t know where to start, you might want to consider working backward to re-enable your business with the right knowledge and direction to move.
Firstly, with digital and physical interactions so tightly intertwined, data can come from all sources of your customer-facing or non customer-facing teams. By identifying who plays a direct role in creating and collating your data sources, users are able to distinguish relevant information for their respective roles. Giving them the knowledge of how their inputs will influence the way you delight customers in the long run will not only drive better collaboration across function, but also rally your troops towards a shared objective.
Secondly, understanding data and processing information should not be a limiting process. A CMO may already have a dashboard and business objectives in mind, but introducing formalized processes can help promote a data-driven culture within the organization. An intelligent insight platform should be able to not only process data, but also have the capabilities to create guided experiences through your data, helping explain the most complex concepts in the simplest manner so that anyone can have access to business intelligence
“If the brains of your business are intelligent data analytics technologies, then marketing and sales automation are your arms and legs, waiting for sensible signals in order to execute their next move.”
Lastly, identifying the right technology mix can be tricky. Most often, service providers or solution vendors provide a piece of the puzzle without fully understanding the greater picture. It is like reading a sign in a different language. However, without your mind’s intelligent processing or the ability to apply meaning to symbolic representation, all your eyes are doing is collecting information about what is in front of you.
Likewise, having an automation tool that just streamlines your data sources and displays them into charts and figures doesn’t necessarily solve your problems of needing actionable insights. If the brains of your business are intelligent data analytics technologies, then marketing and sales automation are your arms and legs, waiting for sensible signals in order to execute their next move.
Deeper insight and best action changes everything
Working with a solution partner who can help you understand and fit the pieces together not only helps you start fast and learn fast, but also pick up the pace to easily address your customers’ needs.
The TIBCO Insight Platform fuses our visual, predictive, and streaming analytics technologies, providing a solution for optimizing business operations. Like a digital nervous system, it lets you build connected intelligence in your business, generate actionable insights in real time, and capitalize on the results.
This article is the first of a three-part series to look at visual, predictive, and streaming analytics technologies can apply to modern marketing.