“I don’t need math to become a marketer,” you scoffed. As a young, naive, marketing major in college, you selectively skirted your way around courses involving math, opting instead for the likes of brand management and marketing communications 101. When you did have to take a math course, you willed your way through knowing that you’d “never have to use it again” once you made the grade. Now it’s 2017, and talk of data analysis in marketing has you scared straight.
(Side note: When I googled “Marketing Degree” while researching this article, one of the first options I saw was a course from NYU offering a BS in Marketing Analytics. Looks like times are a’changing).
According to a recent report by Gartner (available to Gartner clients), “Marketing analytics is booming. Qualified candidates are like the hottest draft picks as need outpaces the talent supply — our data says that 52% of marketing leaders plan to hire analytics talent in the next year[…]”
Cue panic mode: you’re a small business without the budget to hire a data analyst, and you doubt your own mathematically challenged brain to be able to handle the analysis needed to make sense of your marketing data. You’re not alone.
“Marketing leaders rank analytics among the top three most essential capabilities, but almost half (48%) identify marketing analytics as the most difficult skill to recruit and retain,” says Gartner.
I’m here to tell you that there is hope. There are ways that you can make use of the plethora of marketing analytics software tools available to help you track, analyze, and make sense of your marketing data and make informed business decisions.
A report by Gartner (available to Gartner clients) about the basics of data science for digital marketing breaks down the tasks of a marketing data scientist as follows:
- Measurement: Determining the impact of marketing efforts and ad campaigns
- Optimization: Recommending changes in tactics or spending to improve results
- Experiments: Designing and executing tests to isolate causes
- Segmentation: Identifying groups and subgroups of customers and prospects
- Predictive modeling: Building computer models to improve response rates by providing more personalized content, offers, pricing or other treatments, for example
- Storytelling: Communicating messages derived from data to inspire better decisions
Using this framework, I’ll show you how, with the right software tools, you can do your own data analysis in marketing to make sense of and maximize your marketing efforts.
Marketing Analytics step-by-step
Whether you’re trying to see how your AdWords campaigns are running, how people are clicking through on your website, which emails are getting the most opens, or which customers are converting the best: there’s an app for that. As one Gartner report (available to Gartner clients) notes:
“Invest in technologies that enable precision targeting and relevant personalization, along with greater customer-centricity, automation and real-time performance optimization.”
With that in mind, there are plenty of software options that can help you with every step of the marketing analytics process.
Measurement is the first step in determining the reach and effectiveness of your marketing campaigns. It answers questions including how many people saw, clicked on, and converted from various marketing channels. It can show you an overall view of your campaigns, or get more granular to pinpoint exactly which campaigns have garnered the most success.
Software option: Google Analytics
You’re probably already using Google Analytics in some form to track your web traffic, but by setting up tracking and campaign parameters, you can get a better sense of exactly where those ad dollars are coming from. As long as you’ve set up the right tracking for every channel (email, social, paid search), you should start getting a good sense of where most of your web traffic (and money) is coming from. You can also set conversion and funnel goals to see how well your web traffic is converting, or where there might be a hitch in the conversion process. Check out this link for tips on how to set up campaign parameters in Google Analytics.
Experiments are the best way to test something out so that you can catch patterns and prove or disapprove theories surrounding the success of your marketing efforts. This is especially useful when similar campaigns show starkly different results from previous runs. You can experiment with everything from web copy and design, to publishing outlet and publication time. The most important thing to remember is not to be afraid to test things out before you commit– if you’re investing a lot of money in a campaign, experimenting a bit will ensure that you get the best ROI.
Software option: Zarget
Zarget is an A/B testing and heat mapping solution that gives you data about the way that your customers are using your site. Its A/B testing functionality lets you test multiple versions of your web pages, including a web designer to help you change page layout for each test, giving you results on how each variation performed. The heat mapping feature gives you data about where your customers are spending the most time, going as far as giving numerical aggregate click data of the number of people that clicked on different elements of your site.
Similarly, its form analytics show where the biggest holdups are when people are filling in forms and from which step they’re most likely to leave the process.
Once you know what’s working to drive more conversions, you can optimize your website and marketing campaigns based on those results. You’ll want to start spending money in places where you’re seeing the biggest ROI; you’ll want to make improvements to your site based on how people are clicking and what they’re commonly looking for; and you’ll want to send out email campaigns with content that gets the most clicks. You can optimize every part of your online marketing process so that customers have a good user experience while also converting.
Software option: Instapage
Instapage is a landing page platform to design and create landing pages that convert. The first step is building and designing your landing page, which you can do using pre-designed templates or by creating your own design. Once you create your landing page, you can do A/B testing that, similar to the experimentation phase, which will give you results on which pages perform best. You’ll be able to see insights into page performance with real-time reports, as well as add a tracking pixel for conversion data outside of your landing page.
Segmentation not only allows you to separate the proverbial casual shoppers from the qualified leads, it also gives you details about your customers so that you can separate them into buckets and target them accordingly. By knowing who your customers are, where they are coming from, and what their purchase intent is, you’re better able to group them together and identify potentially unmet needs for distinct subsets of customers. These groups can consider anything from demographic info, to past shopping behaviors, to web usage patterns in order to make meaningful subsets out of your customers.
Software option: Autopilot
As a marketing automation platform, Autopilot uses segmentation to target its marketing efforts. Setting up triggers based on user behaviour including whether they opened an email, if they’ve bought a product before, or which page of your website they visit most frequently, Autopilot will automatically categorize people who completed certain activities into distinct segments. It can also pull in customer data from integrations with your CRM or customer support solutions for even more data to populate your segments with.
Although building your own computer model would be ideal, you can still work within your means to make smart predictions about customers. Similar to segmentation, predictive modeling lets you drill down to an even more granular level to identify your customers and target them with the right marketing campaigns that will nudge them to make a purchase. Giving more personalized recommendations, you can use historical purchase and demographic data to identify your sales or usage cycles and then target users based on when they’re more likely to purchase a product or service.
Software option: Radius
Radius is a predictive B2B marketing tool that uses data to give you comprehensive insight into who your most promising customers are, and how best to target them next. It collects and digs up data from other software tools like your CRM and marketing automation software so that you can act on insights and pinpoint the most promising customers. It not only gives you info about your own customers, but aggregates public data from millions of other businesses to give insights into industry trends. It’s go-to-market insights will also help you define customer profiles and identify high converting segments to target.
Storytelling is the oft forgotten step in the marketing analytics process. Collecting data is great, but it’s pretty useless unless you can explain it. Interpreting data can be somewhat of a creative process, but it’ll be infinitely easier when you can see the entire set of data and the factors that affected it in order to be able to provide a coherent narrative to your data.
Software option: TapClicks
Dashboards are a good way to start the storytelling process. TapClicks is one software option that can help. Using its TapAnalytics marketing reporting dashboard, you can collect and populate data from over 150 different marketing platforms, including social media sites like Facebook, Linkedin, YouTube, and Instagram. This data can then be turned into dashboards and graphs that show overall performance of marketing efforts across multiple channels. You can also drill down to individual campaigns in order to get a comparative look at campaign performance, and make decisions about overall marketing strategy based on these reports.
Be your own analyst
Software can’t (exactly) replace a human that’s well-versed in data science; it can’t totally explain and interpret marketing data in order to help make decisions that drive business goals. What it can do is assist less data-savvy marketers in collecting and analyzing some of their online marketing efforts. Analyzing data takes just as much creativity as it does logic, and with the right tools, even old-hat marketers can surprise themselves with how far a little data-dive can go.
According to Gartner:
“Marketing and data science are only just getting acquainted. There will come a time when analytical techniques are built into most workflows and machine-driven decisions are commonplace. At such a time, data science will no longer be a separate activity but the essence of marketing.”
We’re not quite there yet, but it’s important for marketers to familiarize themselves with the budding relationship between marketing and data science in order to stay ahead of the curve and keep their marketing strategy on top of its game.
Looking for more marketing analytics software? Check out some of the options below: