Today, an abundance of data are available for marketers at their fingertips. But taking that data and generating actionable insights to apply to marketing strategies that will impact business results is the biggest challenge. Basing future plans on faulty results can be disastrous so, interpreting your data correctly is critical.
Follow these tips when analyzing your data:
Analysis Paralysis—a Big ‘NO’
Never try to analyze all the data at once. Remember that overanalyzing can become overwhelming and even can result in no course of action being taken. While interpreting data by defining research goals, always try to be strategic. Before you start analyzing your data; try to seek answers of questions including: Which offer is performing the best in market? What marketing message has the highest conversion rate? Or, who is buying this specific product and what marketing channels are they receptive to?
[Read more: Benchmarking – Effective Tool to Grow Your Business]
Try to be Objective
If you have an existing theory, faulty interpretation of data can arise. to interpret data to fit one’s existing belief, confirmation bias is the tendency. This can lead to critical errors in the interpretation of your data. Marketers should focus on these points.
Pick Qualitative Data
Marketers should never avoid taking a look at comments, reviews and other sources of consumer feedback. take the effort to read all the information available on focus groups. You may find interviews or surveys conducted on the particular group. This will prove helpful. For a quantitative analysis, these data can be the inspiration and can also bring insights to the numbers you are reviewing.
Sample Size
A very small data can skew the results and can also bring incorrect results. Smaller samples are misleading and an ‘overly size’ samples can be expensive. There are a few things that you need to determine to calculate your minimum sample size:
- Population Size —How many people fit your demographic in totality?
- Margin of Error —There is no perfect sample actually, you just get to choose how much error to allow.
- Confidence Level —The most common confidence level used is 95%, but others (90%) can also be used.
Marketing Effectiveness Measure
Access the performance of each marketing channel, marketing message and audience involvement. You may find some obvious optimizations that can be made at once. Examine the data and results to determine how each metric can be improved after benchmarks are determined. From all angles take a look at the data. Through additional testing, you can see how to optimize your channels, and also change your marketing message and offers, or make shifts from your target audience. Conversion rate, total revenue, average order value, orders completed, cart abandonment rate, drop-off rate within the checkout process, visits, page views, leads generated, click through rate, and orders completed are some examples of measurement.
Data Optimize
You will get insight into who is responding, what offer is enticing your consumers, and the channels that are moving the mark through each and every test that has been performed.to make shifts to your marketing plans, use this information and measure and repeat this.
If you are a marketer, who is dependent on data for more meaningful marketing decisions, you can contact Market Quotient-an online research firm. Our experts with their outstanding analytical knowledge ensure you get high-end solutions and take a step ahead towards your success.
