Data analytics in marketing interests and fascinates almost all marketers and even people who don’t have anything to do with this field. Marketing data analysts aren’t magicians who turn numbers into cash. But rather they are specialists who try to answer the two main questions – why X happened and what to do to achieve Y.
As a short intro, we want to share examples on how 3 companies use data analytics for marketing:
Sunny Ashley, Founder at Autoshopinvoice says they have leveraged data in shaping their SEO strategy. Their data taught that for their niche blog posting frequency doesn’t have a huge impact on SEO metrics, while post length and quality do.
Manny Hernandez, Co-Founder at Wealth Growth Wisdom says the best part of using data in marketing is knowing exactly who your audience is. You can track the type of visitors that come to your site and build personas around those who engage.
Nicholas Bond, Marketing & Data Specialist at Renovation 320 says data analytics in marketing is important for two reasons. First, it allows to track marketing goals and spend. Second, it shows which marketing channels are producing not only the biggest quantity but also the most quality leads.
Our colleagues shared these specific examples with us. If you want to get acquainted with broader cases (with examples, of course), keep on reading!
#1 Understanding how your website performs
Evaluating your website performance is so important and sometimes so time-consuming that even digital marketers exist with the job title “Web Analytics Specialist”.
Every session that starts on your website, every click, every lead that is generated is a piece of data. And what answer you will receive depends on what question you will pose.
For example, you are planning to translate your website. You definitely won’t pick random languages without checking out your Google Analytics.
First, you will visit Audience->Geo->Language to see which languages your website visitors speak. You should also check out the Location tab because people may be speaking more than one official language in a single country.
#2 Understanding whether your customers are satisfied
Do you receive written reviews, comments, recommendations from your customers? They are pieces of data.
Do you receive the same information orally? It’s again data. The main difference is whether the data is quantitative (structured) or qualitative (unstructured).
For example, if your customers rate your product with a 5-point scale, every point is quantitative data. You have numbers – fixed variables to work with.
But when someone writes “Excellent service. I will definitely come back and refer my friends”, it’s qualitative data. And it’s you who should regard this review as “5 stars”.
Quantitative data is easier to organize, analyze and it helps understand the full picture of how your customers feel about your company. But to actually reveal the strengths and weaknesses of your business, you need to explore what words and phrases people use, aka pay attention to qualitative data.
#3 Understanding which types of posts users want to see on your social media profile
When you just start working on your social media marketing strategy, it’s easy to find post ideas on the internet. Thus, you can couple expert advice with your audience’s interests and seems like you found the way to drive engagement.
But the real-life SMM is a bit more complicated, requires constant monitoring and posting what your followers actually like.
For example, for one of our clients we were trying to understand which social networks bring the highest traffic and which posts drive more engagement.
We found out that the traffic is mainly coming from Twitter. So we started publishing more posts with link previews on this platform.
We also noticed that publishing infographics on Instagram brings the highest number of interactions among all social networks. So we started regarding Instagram not as a medium for getting clicks but one that drives impressions and engagement.
You can understand what works for you after checking out the reports presented by your social media scheduling tool.
Impressions, clicks, interactions, number of new contacts are your pieces of data, while you are the one who should interpret what’s going on and what to do next.
#4 Understanding how your paid ads perform
When you launch your PPC campaign, you can track the ad campaign performance and make changes both manually and with the help of software (check out this article if you are going to run PPC ads for your SaaS company).
The same approach is available when you are running social media ads.
For example, Facebook is the social media channel from where marketers generate the highest ROI. It automatically improves the ad performance – selects where the ad should be placed, with which creative, etc.
But if only Facebook’s optimization features aren’t enough for you, you can use a third-party tool that automatically creates ad variations, optimizes your ads, etc.
As you can see, optimizing your paid ads performance requires less intervention from your side than when you track the performance of your social media posts. But it doesn’t mean you should sit back and rely only on tools.
Sometimes even paid ads require human presence and there are things tools can’t understand without a command.
For example, if people are hiding your Facebook ads (this is your data), it’s a sign that the same users see it too frequently. So you should tell Facebook not to show the same ad to the same people more than 2-3 times. You received the piece of data, you analyzed it, you told the platform what to do.
#5 Understanding how to segment your subscribers/leads
Segmentation can become a life-changer for businesses with multiple buyer personas or with multiple stages in the buying process.
For example, if you are an online store and sell products both for men and women, you can’t send the same emails or text messages to all of them. This is the simplest example. Not to mention the fact that your male and female customers are probably of different ages and prefer different fashion styles.
Every information you have about your customers (gender, age, style preferences and even buying frequency) are pieces of data. And the more details you know about your buyers, the easier it is to segment them, put relevant offers in front of them and increase conversions.
Or let’s say you are a SaaS company who has a 3-stage funnel (Awareness, Consideration, Decision). Visitors who download Awareness stage content shouldn’t receive the same emails as Decision stage visitors. Well, you might send a webinar invitation or Christmas wishes to your whole contact list but these cases are exceptions, not the rule.
Depending on who your leads are and how close they are to the BoFu (aka becoming paying customers), you should segment them accordingly.
Using data in marketing for your digital strategy
Do you already have data analytics tools set up for your digital marketing strategy? Are you using them effectively? Contact Andava’s team, share your challenges and our experts will help you bring data analytics and marketing together.