Data analysis is defined as a process of inspecting, cleansing, transforming, and modelling data with the goal of discovering useful information, suggesting conclusions, and supporting decision-making.
At Freespee we process and manage a significant amount of data from our significant client pool. Data is our bread and butter. Therefore to sort through our cache, we have Alice Lamy, our resident Data Analyst.
Alice was born in Montreal, Quebec — a province nestled in the Great White North (Canada). She then migrated to France with her family at ten-years-old.
Since then, she completed a Bachelor’s in Communication Science at the University of Montreal and a Master’s degree in Persuasive Communication at the University of Amsterdam, focusing mainly on consumer psychology and different modes of persuasion in advertising and health communication.
We caught up with Alice in Freespee’s London office to touch on the inner workings of data at a cloud communication platform like ours.
Freespee: Hey Alice, so what does a Data Analyst do?
Alice: Hey! I analyse data to gain useful insights on both Freespee and our customer’s behaviour and performance. We work with statistics in our own platform, but also use external tools like Tableau and plain Excel to develop different variables from which we pull numbers to produce relevant information.
Freespee: How do you turn data into concrete and useful information?
Alice: I think the most important thing to have before you start analysing is a hypothesis to achieve the right calculation. The way it works is that you have a dependent and some independent variables. If you have an idea of what could be the relationship between these variables, you can start to do your analysis.
For example, if a customer wants to understand what drove people to call their business, I can look at what might have influenced a good or bad performance. It can be many things from business hours, business days, online advertising, click to call to the different regions or countries the call is coming from.
Freespee: How important is customer data to the growth of a company?
Alice: I think it’s essential because it helps you understand more about the consumer lifecycle, and it definitely helps the customer success team offer up advice and ideas to solve business problems more creatively.
Internally, it also helps us manage the business, and get an idea of where we stand as a company and how we are performing with our customers so we can evolve and become more aware of their needs.
Freespee: Would you say it’s a great predictor of behaviour?
Alice: Yes, it’s really insightful. It is a way to give very good insights on consumers’ wants and needs, but it has its limits. We can predict what will drive them to call your business, but there are always going to be inconsistencies in behaviour. What is so interesting about humans is that you can never be 100% certain what they will do, need or want next.
Freespee: How do you define big data?
Alice: Big data can be a confusing term in my opinion, as I think there are so many ways you can define it and it depends on the context. At university, for example, we were using Python to do some “sentiment analysis” derived from Twitter posts during Donald Trump’s election. Big data can, therefore, be a lot of things, and you can find many tools to analyse it.
In the context of Freespee, big data is handy for us to know more about our customers: analysing performance and trends thanks to the use of our platform (CTR, which campaigns drive calls, what people call about, etc.). This kind of data helps us understand how to solve our customers’ business problems better and how our service can enhance sales performance or brand awareness.
We also use big data to know more about where Freespee stands thanks to Salesforce: how sales are growing, how we are taking care our current customers, how we are dealing with prospects, etc.
So big data is a collection of data from different sources that allow us to discover and analyse so many different sides of our business.
Freespee: What is the hardest data to analyse?
Alice: To me, the analysis part is probably the most natural part of the process of using data. As long as you know what your research question is, and what you want to verify, it is quite straightforward. However, collecting and cleaning the data can be a pain, and you need a lot of patience to end up with clean and easy-to-use data.
No one can deny the importance of data in our lives, sometimes however it can overwhelm us. Luckily we have professionals like Alice to make sense of it all. Thanks Alice!
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