The following is a guest post from Jill Johnson, Director of Data & Analytics for Strategic America.
For most modern marketers, an abundance of data is now available at their fingertips. The big challenge is taking that data and generating actionable insights to apply to marketing strategies that will impact business results.
Interpreting your data correctly is critical basing future plans on faulty results can be disastrous. Here are some tips to consider when analyzing your data:
Avoid Analysis Paralysis
Don’t try to analyze all the data at once; overanalyzing can become overwhelming and result in no course of action being taken. Be strategic when interpreting data by defining research goals. What questions are you trying to answer: What does my best customer look like? Which offer is performing the best in market? What marketing message has the highest conversion rate? Who is buying this specific product and what marketing channels are they receptive to?
Faulty interpretation of data can arise if you have an existing theory. Confirmation bias is the tendency to interpret data to fit one’s existing belief. This can lead to critical errors in the interpretation of your data.
Include Qualitative Data
Be sure to look at comments, reviews and other sources of consumer feedback. If focus groups, interviews or surveys were conducted, take the time to read through that information. This data can bring insights to the numbers you are reviewing or can be the inspiration for a quantitative analysis. For instance, a comment about long wait time can spur an analysis of the number of lost sales in conjunction with delivery time.
Sample Size Matters
If the data that you are analyzing is too small, it can skew the results and lead you to an insight that is incorrect. The larger the sample size, the more accurately they reflect the population. Small samples are misleading and an overly large samples can be expensive to market to. How does one determine a big enough sample size to extract accurate insights from? To calculate your minimum sample size there are a few things that you need to determine:
Population Size — How many total people fit your demographic? For instance, if you are analyzing homeowners that live in Nashville, your population size would be the total number of homeowners in Nashville.
Margin of Error — There is no perfect sample. You get to choose how much error to allow. The confidence interval determines how much higher or lower than the population mean you are willing to let your sample mean fall.
Confidence Level — How confident do you want to be that the actual mean falls within your confidence interval? The most common confidence level used is 95%, but others can be used, for example 90% and 99% confident.
There are several online calculators that can help you though this process. The following link is one https://www.qualtrics.com/blog/calculating-sample-size/
Measure Marketing Effectiveness
This data will provide you with key insights as to what is performing, and what is not. Popular metrics are: cost-per-call, click-through rates, cost per appointment and return on marketing investment. It is important to access the performance of each marketing channel, marketing message and audience. Often you will find some obvious optimizations that can be made at once. Once benchmarks are determined, examine the data and results to determine how each metric can be improved. Look at the Data from all angles – ask Why? Where are the biggest data opportunities? What questions need to be answered and determine a plan for further testing? Additional testing can show you how to optimize your channels, change your marketing message and offers, or make shifts to your targeting. Some examples of measurement: 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.
Each test performed will give you more insight into who is responding, what offer is enticing your consumers, and the channels that are moving the mark. Use this information to make shifts to your marketing plans; measure and repeat.
Marketers depend on data for more and more of their marketing decisions. Pressure to deliver business results have never been higher. Technology adoption is accelerating and changing consumer behavior. Marketing leaders that are analytical and data-savvy are in high demand. Making the link between the data and an actionable insight is critical for business success.