Now that you know how to choose the right paid search campaign type for your business, how do you know that it’s actually driving revenue? To accurately measure the ROI of your paid search campaigns, you need to be able to find the right metrics to measure, choose KPIs that match your business objectives and align your reporting with the needs of your stakeholders and marketing leadership. If you are using paid search to drive phone calls to your business, you’ll also need to make sure that your call analytics data is properly utilized to measure conversions that happen on the phone.
With these tips straight from the great minds at Think With Google and the call analytics experts at Invoca, you can more accurately measure your paid search impact on the bottom line.
Why Call Analytics Data is Needed to Measure Paid Search ROI
If you are spending marketing dollars on paid search to drive sales calls, just knowing that a campaign drove a call is not enough information to work off of. You need to know exactly what campaign and keyword drove each call and then you need to be able to tell if that call turned into a sale, appointment, quote, or whatever you consider to be a successful conversion. More importantly, you need to know if you’re bidding on keywords that are driving the wrong kind of calls.
If you are just looking at data from Google Ads and Google Analytics, you might be able to see that a campaign or keyword is driving calls and say “great, I’m awesome, high-fives for everyone, let’s go to happy hour!” Contain your thirst for a moment, because those calls you’re counting could be anything. They could be sales calls, but they can also be customer service calls, people asking for directions — anything but an actual conversion.
To show how important call attribution data is to measure ROI, we’ll use Invoca customer Ydesign Group as an example. This online high-end lighting and furniture retailer spends a significant amount of its budget on paid search to drive calls to its call center. But it turns out they were putting much of it in the wrong places. “We were bidding to be the first or second search result, and the costs-per-click were some of the highest in our paid search campaigns,” said Jesse Teske, web analytics manager at YDesign Group. “But we discovered that the ad spend wasn’t driving call conversions. Most of the calls we received were for customer service or replacements.” Using call analytics data from Invoca, they were able to dial back of ad spend on underperforming campaigns and put more money behind keywords that drive revenue, not customer service calls. As a result, they saw a year-over-year efficiency gain in ROAS of 37%, on average.
By integrating your call tracking and analytics platform with Google Ads and Google Analytics, and your CRM, you can not only prove that conversions are actually happening, but you can attribute the sales directly to correct channels, right down to the keyword.
Okay, now that you know why call analytics data needs to be part of your ROI-proving package, here’s how you can make sense of all the data you have and become smarter at measuring the bottom-line impact of your advertising courtesy of the analytics experts at Google along with some tips on integrating your call tracking data into these strategies.
1. Classify advertising metrics based on their business impact
Data is only a means to an end. The end goal is not to create a pretty chart showing how many impressions different campaigns got. It’s to have an impact on the company’s bottom line. To separate the wheat from the chaff, at Google, we classify the tsunami of metrics at our disposal using an impact matrix.
Here, the x-axis indicates when a metric becomes useful. For example, impressions are available and useful in real time. Some elements of customer lifetime value are also available in real time, but it takes months for them to be useful. Organizing advertising metrics in this way helps to classify which ones to pay attention to and when.
Call Tracking Data Tip: Conversion data from Invoca can be pushed to the Google Ads platform to make keyword bid adjustments in real time.
The y-axis above — on a logarithmic scale to sharpen its value — indicates whether a metric is tactical or strategic. Sticking with the same examples, impressions are super tactical and add, at most, pennies of value to any decision made. Customer lifetime value, on the other hand, is super strategic. The insights gleaned from this metric can add hundreds of thousands of dollars of value to any decision made.
Once you’ve classified your marketing metrics in this way, your reports and dashboards will be cleaner, your marketers will have 50% less data to wade through, and your analysts will have 50% more time to spend on carrying out analyses (as opposed to just data puking).
2. Choose KPIs with business objectives in mind
Marketers often use the terms “metrics” and “key performance indicators” interchangeably, but they are entirely different things. A KPI is a special kind of metric that helps you understand how you’re doing against a specific business objective.
The reason it’s important to remember this distinction is that, when we don’t, we can end up setting KPIs that don’t actually tell us if a marketing campaign is helping us hit our business goals. Why? Sometimes we’ve chosen a metric because it’s easy to measure, other times we haven’t taken enough time to think about what we’re really trying to achieve.
That’s why my team took all the marketing metrics we track at Google and worked out which ones make the most sense as KPIs for different types of campaigns. We then ranked them in order of effectiveness, with gold being the best of the bunch.
So if a marketer at Google is running a brand campaign, and their goal is to generate awareness, we’d rather they track how often an ad was audible and visible on complete (AVOC) than how many impressions it got, since we know from internal testing that this is a more accurate predictor of brand awareness lift.
Of course, coming up with KPIs that really measure whether you’re achieving your business goals is hard. This simple five-step digital marketing and measurement model that I developed should make that process easier. The end result will be a one-page document that can act as the north star for your entire company’s marketing analytics efforts.
3. Align your analytical output with each leader’s altitude
Last year, my team did an audit of the marketing metrics that were being reported back to our CMO. The number we got back — which was a conservative estimate — was 70. Marketing leaders need to make strategic decisions about where to invest and where to scale back. A data dump of every metric available is not going to help them do that.
That’s why, here at Google, we’ve taken all the data points from our impact matrix and divided them based on who needs to take action on them. Metrics in the bottom-left side of the impact matrix — click-through rates, unique page views — help make small decisions in real time. As far as possible, we’ve automated all the decision-making related to these metrics.
Call Tracking Data Tip: Instead of dumping call tracking data at the feet of your CMO, it can be used to calculate and reinforce your ROI and ROAS numbers. Since Invoca is providing call outcome data, you have a precise way to show that your marketing campaigns are performing and delivering revenue.
We then selected a handful of relevant business metrics from the top-left and bottom-right side of the impact matrix for our managers and directors to focus on. These are high-value metrics that might take time to become useful and need human contextual interpretation. The top-right section includes the metrics that can potentially have an enormous strategic impact on our business. These are the ones we share with our VPs and CMO. Each individual receives just the data they need for the decisions only they can make to deliver incremental impact.
It’s not how much data you have that matters, it’s what you do with it. I hope these three steps will help you do something better with all the data you have at your disposal.