Data, data everywhere

What is data?

We think of data as raw information, and it can come in a variety of different formats. Most people think of data as endless excel spreadsheets, and those people aren’t wrong: that is data. But before it ends up in a spreadsheet or a database somewhere, those individual data points can be found in so many different places.

Social media is a good example of this (e.g. Twitter). Where the average person sees Tweets, links and images, a data scientist sees mountains of data regarding how people feel about certain topics, what words they use to describe those same topics, and even how people’s perspectives change over time. And that’s just scratching the surface.

What is data science?

Data science is the practice of extracting value from data. We tend to refer to a single piece of value as an insight.

There’s a whole host of different ways to draw out insights from a dataset. These might include:

• Graphs & visualisations
• Statistical analysis
• Machine learning
• Forecasting

The key takeaway here is that data science means distilling data down into information that is both meaningful and useful.

What does it mean to be data-driven?

Broadly speaking, we tend to think an organisation is data-driven if they:

1. Leverage insights from data
2. Inform decision making with empirical evidence
3. Never analyse data in a vacuum.
4. Have team buy-in for using data

This clip explains each point in a bit more detail:

3 big ways to be data-driven

We think that investing resources into these three areas will provide the most value to most types of organisations. Here’s the breakdown:

1. (Really) know your customer

Do you really know your customers’ characteristics? Can you break your customer-base down into smaller subsets of customers that share similar characteristics, otherwise known as customer profiles? This is what we like to do with data.

These profiles are made up of demographic data (who people are), psychographic data (what people think) and behavioural data (what people do). Each layer helps form a more complete sense of what makes each customer tick. Knowing this data hypothetically helps you to get in front of your customers at the right time in an ideal context to engage with them.

Click here to understand more from the session.

2. Business analytics & reporting

Source: Jacob Olsufka on Tableau Public

Augmenting your operations with analytics, dashboards, and insights reports can be a gamechanger for a number of reasons.

Analytics show you your organisation’s health and let you get as close to the pulse as possible.

Dashboards are also great for transparency and oversight at a glance. They save countless hours and reduce the risk of uninformed decision-making.

Click here to understand more from the session.

3. Making insights actionable & accessible

Ever seen a visualisation like this? Not very helpful, is it?

When communicating with data it’s incredibly important to consider two things:

1. How accessible insights are to your audience; and
2. How actionable your insights are.

Click here to understand more from the session.

Quick data wins: steps you can take tomorrow

Let’s wrap things up with steps you can take right now to start becoming a more data-driven organisation.

Data stocktake

Make a list of all the places you’re currently collecting data, or have the potential to collect data. We call these data sources.

For each data source, list what type of data you can capture (variables) and how you think you could use that data for some benefit. Then ask yourself whether your organisation is already leveraging the data in the way you’re imagining.

This list will give a really useful starting point for what data you’re currently leveraging and what data you’re not. Coupled with the next quick win, it’s a game-changer.

Click here to hear more.

Key decision review

A key decision involves getting managers, team leads and executives in a room and asking: what key decisions do we make on a daily, weekly, or monthly basis?

You then ask: how can data inform these decisions?

It’s a great way to ground your data analysis in what’s important.

Click here to understand more from the session.

Review customer profiles

Like what we spoke about earlier regarding knowing your customers, this activity involves reviewing whether or not your current understanding of your customer base is informed by data.

If your marketing team finds it difficult to answer the question “what evidence do we have that our customers actually have those characteristics?”, then you might be due for a review of those customer profiles.

Data upskill

If you’re not confident with your team’s level of confidence or understanding of the potential of data, you can always engage some data scientists to upskill them.

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If you want to learn more from the WhyHive team about how to become more data-driven, please contact Matt Cohen or you can book a Discovery Session here.

After back-to-back webinars, the next Connect The Dots session will (touch wood) be an in-person session on Thursday, March 10th (venue and topic TBC) when - in the nice segue from data science - network partner Starburst Insights will be exploring the world of brand research and looking at ways your business can develop insights to latch onto.

To receive the registration details in early next year and/or to be kept across any future sessions, follow this link.