By Ray Estevez
Chief Information Officer, True Influence
The digital transformation has made every company a data company and turned data fluency into a must-have skill.
Sure, you may not produce and sell data technology solutions. But if your organization markets and sells to other businesses, data fluency will help you make decisions faster and target the right audiences. To do that, you must master the tech that drives Big Data. And that takes skills.
Not every business is tackling this evolution the same way, of course. Larger companies build out their own data science teams and create custom artificial intelligence (AI); mid-sized and small enterprises still rely primarily on third-party tools to do the heavy lifting.
But every business needs to grow its data skill sets, either internally or externally. Being able to batch process large volumes of data is yesterday’s table stakes – you have to be both quick and smart, and that requires a mix of expertise and powerful tools.
In this post, I’ll take a look at the key data fluency skills that need to be baked into sales and marketing operations, as well as where they probably ought to live within your company structure. There’s no one-size-fits-all model, of course, and the Big Data landscape is rapidly advancing. But as you look to add new team members or partners, these are the critical capabilities to build upon.
5 Things Everyone Should Know about Data Fluency
If you look at any article that lists top “X” skills every marketer must have for 2021, you’ll invariably see “data” or “analytics” listed as a must-have. While I certainly agree with the sentiment, these kinds of lists typically don’t spell out what these capabilities actually are.
Some skills are highly specialized, obviously, but everyone involved in marketing and sales needs a basic understanding of these five essentials of business data fluency.
1 – What types of data does your organization use? Everyone should be able to quickly recall the categories of data you gather about customers and prospects. They should also be conversant in the half-dozen or so specific data points (frequency of site visit, average purchase size, etc.) in your mix.
2 – How do we use that data? Even if they can’t decipher the precise algorithm, all marketers should know the core value and applications of your data. What does “time since first purchase” typically reveal about an account’s current buy cycle? Every data-fluent marketer should be familiar with the half dozen or so key performance indicators (KPIs) that drive their business. If you don’t understand the current value of data, you won’t know how to extend that value into new revenue streams. Make current value your starting point.
3 – Where does the data sit? Is the data stored locally, in the cloud or in a hybrid model? What tools and platforms are available to sales and marketing to access data?
4 – Who can get you access to information? Nobody likes the politics of data silos, but there are good reasons to limit access to some information. Who governs data at your business, and what are the proper channels to request access? These are key pieces of knowledge for every marketing team.
5 – How do we build tools that make it easier for marketers to engage with raw data? Who actually has the skills to build queries and dashboards? Again, the specialized skills involved in creating tools can live in different teams, but every marketer should know where to go with their bright idea for a new segment or report. And every marketer, regardless of company size, should know how to use the tools they have.
Data Fluency by Skills
In general, you can describe data skills by these categories:
- Data processing
- Streamlining manual data ingestion
- Loading data
- Matching and query logic
- Data analytics and modeling
All of these are becoming more critical to organizations, either with in-house skills and solutions, or via outsourcing to trusted vendors with powerful GUIs or managed services.
What’s Your Data Fluency?
Regardless of company size, marketing and sales know they must be more fluent in data, and skill levels are rising. That doesn’t mean every copywriter has to architect a data lake, obviously, but over the next few years, having more advanced data tech skills within marketing will become the norm, not the exception.
Some data tasks – mostly relating to storage and security – will likely remain in IT. Data loading is largely still a tech job, although with distributed tools and validation jobs more trained staff can be trusted to input data. And an increasing number of enterprises are creating independent data teams that focus on governance and analysis.
In Part 2 of this blog, we will take a quick look at where key data skills should live in your organization, based on size and general technical expertise.