Do you have too much data? Do you know how to get the best out of your data? How do you work out your target market, or how to contact your target market? Do you analyse the data that you have access to? Do you review your data at face value?
This is a simple guide to help you understand your data and what to do with it.
To succeed as a business your data needs to be accurate, and you need to interpret your data in the correct way to get the best possible outcomes out of that data.
Firstly your data needs to be 100% accurate to meet the purpose of having that data. For every consumer, customer and stakeholder at your company you need to ensure that you have the correct types of data needed. For example, if you wanted to know how many female consumers your company has, then you need to ensure that every consumer states their gender, and set this as a mandatory field within a survey or a subscription.
How do you collect this data? Your data capture could come as a result of a survey or through a subscription.
If it is through a subscription, then you should look to make almost every field mandatory in order for you to fully capture all of the data necessary, if a field is not mandatory then most will leave this empty.
If it is through a survey, then how do you communicate this to your customers? You will need to operate across all forms of direct and indirect advertising tools to gain the maximum possible capture. Indirect marketing needs to be continuos over the period of time that the survey is available to complete. Direct marketing should not be as consistent, as overloading the customer with reminders to fill out a survey will only deter them from completing the survey.
To be able to make informed decisions from the data captured, you need to be able to understand the data gathered. One lesson to learn from data analysis, is to not interpret the data at face value. For example, if you have surveyed 100 people, across many organisations, with more than 1 person answering from each organisation and you ask them a question relating to the type of social media that they use, and they can select more than one option; 45% say that they use Facebook, 27% say that they use Twitter and the rest state that they either don’t use social media, or that they have not answered the question.
You cannot interpret this data to fully mean that 45% of all customers questioned use Facebook and that 27% of those customers use Twitter instead because not enough information has been gathered to presume this hypothesis.
There are a series of questions to consider:
- Has everybody answered the question?
- How many different organisations have answered the question?
- Do 45% of customers use Facebook and 27% use Twitter instead?
- Do 45% of customers use Facebook and 27% use Twitter as well?
- What do they use the social media platform for?
- Do they personally follow you on Twitter or Facebook?
- Does the organisation follow you on Twitter or Facebook?
Question 4 is key. They may only use social media to post, they may not browse the social media, meaning that they may not actually come across anything that you advertise on social media. Do they personally follow you? If they do then they will more than likely, browse social media and will come across your adverts. If the organisation follows you only then who will see what you advertise within that company? Will they react to the things that you post?
To fully understand how to make the most out of social media in this example, you need to know the above information otherwise you are still only roughly estimating how to react with social media in order to gain your customers attention. This information may be gathered through a series of follow up questions. You also need to understand who actually answered the social media question, it could be that 5 people from the same organisation have stated that they use social media, thus pushing up your percentage of users however that is only 1 organisation. To capture this information you may require them to state their organisation when submitting the survey, and for this information to be shown across each question in the survey so that you can fully understand the trend.
If you cannot gain all of this information then you need to understand that you cannot review the data at face value, and that you need to understand other factors that may have affected the answers that you have collated. You can only estimate how to react to the answered question with this little information.
Acting on results before another survey
You may produce a yearly survey for customers to complete, which by the way is absolutely fine, as long as you can present to them what you have done since your last survey.
If you ask your customers, consumers and stakeholders to complete a survey and then a year later you ask them to fill out another, then they will be more unlikely to fill it in or provide accurate answers if there has been no communication from your organisation in regards to the last survey.
After analysing all of the data, you need to tell your customers, what you will do on the back of the results, what you have already acted upon, and show them the results from these actions. This way the customer will see a purpose to the surveys and feel that their feedback is valued, this will then encourage them to fill in another survey.
As an organisation, you need to provide yourselves with enough time to implement any actions that are necessary prior to another survey going out to customers. If you implement certain actions 1 month prior to the second survey being completed by customers, then they may not fully see the benefit of these actions for months after they have completed the second survey.
You may then find that the trend in answers is very similar to the previous survey because they haven’t seen the full benefit of the actions just yet. This would then make your third survey’s results very different to the first and second survey which would make you wonder why there is such a disparity in correlation between the first two surveys and the third survey.
There are many different forms of capturing data, but the key is that the information provided is 1 – accurate, and 2 – exactly what you need to fully appreciate the data and act upon it.
Analysing data is a complex exercise, and it is not for the light hearted. You need to fully appreciate the reasons that certain answers have been given and not judge the answers at face value.
Another example of this; a football club may announce that they have made a loss for the financial year, and most people would look at that and say that they are in trouble financially. But the case may be that they have spent more in the final quarter of the year in order to improve their market positioning and to improve their finances long term, and within a year, they may be back in profit and you could not foresee this because you only looked at the main point – that they had made a loss.
Data can be interpreted in many different ways, and you need to open your mind when analysing the data because any implementation needs to be correct following the survey.