3 Analytics Tips To Give Your Lead Generation Program A Facelift
Marketers and business owners continue to spend a lot of money driving traffic to their websites and yet many struggle with lead generation and optimizing the traffic and conversion from the campaigns that they are running. Read these three tips and take your lead generation program to the next level.
1. Focus on Key Metrics
What Key Performances Indicators (KPIs) lead generation marketers and business owners should pay attention to.
2. Content Consumption and Optimization
We spend a lot of money developing content, such as webinars, whitepapers and content for website(s). What content do our visitors consume and lead to more engagement? Is this content helping convert traffic to leads?
3. Segment Your Campaigns
Segmentation is a powerful concept in analytics. Learn how to segment your campaign and how to have full visibility for what’s driving leads your business.
4. (Bonus) Advanced Optimization Techniques
1. Focus on Key Metrics
Metrics are abundant and everyone can have easy access to enterprise-level analytics solutions. As a matter of fact, millions of sites run Google Analytics and marketers leverage its user-friendly interface and robust reporting capabilities.
In Google Analytics, you have the ability to see what channels and marketing initiatives bring you leads, see what pages are being viewed, and what interactions users are taking, and also measure task completions such as downloading whitepapers, registering for a webinar or lead capture.
This is a blessing for us data geeks and could be a curse for those who just don’t have the time to dive in the ocean of data and metrics. But as the saying goes “No pain, No gain.” You must allocate some time to track your lead generation programs. The key is to focus on a few metrics that impact the bottom line. Here are some examples for specific engaging actions:
- Form completion (Lead)
- Watch a video
- Subscribe to newsletter
- Become a member
In addition, you should closely monitor your traffic sources, your paid search, your SEO and your email traffic. All of that is available to you. Any report that you want in Google Analytics, you can export into a pdf or have it emailed to you. You don’t have to log-in and find that report saving time to nurture your leads.
Look at the visits: Am I getting new visitors? Or is it the old returning visitors? Am I nurturing my existing visitors to come back? Am I retaining enough? Segment your traffic by new vs. returning and see where things are heading.
We also want to look at the engagements. It’s one thing to draw traffic to a site, but if visitors are leaving right away or they can’t find what they are looking for, there’s something wrong.
Time on site: Are people spending more time on my site and doing something useful, like downloading, or viewing a video, or subscribing to an email newsletter? So look for those types of engagements. Examine the number of pages per visit, look at video views, and look at downloads. All these are very good indicators that your visitors are engaged with your website.
And last but not least, look at your conversion rates. Basically, of all the traffic that I’m getting how much of that is converting into leads. For instance, if I have a hundred visits today and I capture 10 leads, then that’s 10% conversion rate. Track your conversion rate and keep an eye on it. This is where you can find issues or find underperforming campaigns.
In addition to that and to make your job easier, you have the capabilities of building very nice dashboards in Google Analytics. Here is an example:
2. Content Consumption and Optimization
Content is and has always been king, for as far as I remember. Having a plan to measure what your site users consume is essential in this content marketing age, where every business is a publisher.
In Google Analytics, you can leverage a mechanism called Event tracking. You basically track user interactions with Events: If I click on a button, if I click on an expand icon, if I download an image or if I download a whitepaper, all that is trackable including Videos, Downloads, Outbound links, Outcomes. Let’s take a look at an example:
We had a total of 7,095 Events: One Event category for Video and another Event category of Downloads. As you can see we have 6,361 interactions with the video, and 734 downloads.
We can now assess the performance of this content, for example: are the download buttons/links prominent? For video analytics, we can dig deeper and see what percentage of viewers completed the entire video. And we can see in the above snapshot that out of the 6,361 video events, only 585 completed the video all the way to the end.
We can even drill down and view which specific video people interacted with and which they didn’t and then produce more engaging videos for the types that your clients liked.
3. Segment Your Campaigns
One can’t emphasize segmentation enough, it is key to analytics and to marketing in general. With segmentation you’ll be able to separate the type of traffic that you’re getting. For example:
a. segmenting paid-search traffic versus SEO traffic
b. new vs. returning visitors
c. fall campaign vs. fall campaign from last year
d. traffic from Canada vs. traffic from US
All of these are examples of the way data can be segmented so that it’s a bit more actionable and a bit easier to analyze.
Take a look at this case study where the client had a high cost per conversion, but where do we start, how do we go about improving (lowering) the cost per conversion? Trend and segment!
In the illustration below, we see, in August the cost per conversion was a bit over $80 and for October, it was about $100. But then if you look at the data further, you see that we significantly improved, down to $30 per conversion!
The optimization did not happen overnight. It took a bit of time but we have 5-times the improvement in terms of cost savings. The way the client approached this optimization initiative is: they segmented their campaigns and asked where they were spending a lot of money with minimal or low return? So instead of showing all their August data aggregated, they reported on data by campaign, by channel. They saw that a whole lot of traffic and conversion from Google Display is coming at a very expensive rate, almost $260.
The client immediately started to look at the landing pages for this channel, and also examined the campaign, ad-targeting, call-to-action and the offer to draw people to the landing pages. And it took them a bit of time, some ups-and-downs but eventually they were able to bring down the costs across all their channels to below $50 per conversion.
The important part in this concept is to look at every channel that you have and not just at an aggregate and say I have this many visits. I have a link here to help you track those different channels or different campaigns so that you can report on them accordingly:
As marketers, one of the challenges that we face is that we sometimes just look at one-data source. I look at Google Analytics and think that’s sufficient. Now, Google Analytics is amazing and I encourage you to use it. But I also want to highlight some of the missing data that you want to get from other systems, namely marketing automation platform (Marketo, Act-on, etc.) to attain meaningful reports after a lead is captured. Let’s take a look at this example from another organization that is capturing leads on this form:
When you look at the data in the backend, CRM or the marketing automation system, 86% of those leads were unqualified, pure junk or spam leads or contacts that are not fit for what the company offers. On this form, I’m just reporting on my conversion rate, it’s not really meaningful. This single source reporting is actually misleading. The key here is to join the data from the two systems (Google Analytics and your CRM or Marketing Automation System) to make sure you are reporting on the qualified leads. That’s what really matters at the end of the day.
Any time you start bringing data from multiple sources, it’ll take a bit more process and time. You might have couple of Excel spreadsheets, or join the data in Tableau or whatever system you are using. You have to pull that data from two different systems to start painting a better picture, a bit closer to the 360˚ view of your prospects!
This type of tracking and type of investment, time and effort will give us a significant increase in the number of leads and a significant decrease in the cost of those leads.
4. Bonus – Advanced Optimization Tips
I want to conclude with a couple of advanced tips.
It takes more than one visit to convert
One is the Multi-channel Funnel (MCF) reports in GA, where you can see previous interactions that the visitors took on your site before they converted. So you see here, for example, on line 4, somebody came to the website through a paid-search campaign e.g. Google AdWords, and then they left. Then maybe a week later they visited the site again from an organic search and then they converted.
So understanding that people, come to the website multiple times before they convert is important. This is the behavior that most of exhibit when we buy nowadays. Understanding this cycle and all these touch points is essential. You can leverage the Multi-channel Funnel reports in Google Analytics to get this kind of visibility.
The Multi-Screen world
The other significant aspect is understanding the Multi-Screen world that we live in. People come to our websites from mobiles devices, from desktops, from tablets, so recognizing that, for example, of the times that people are watching TV, 77% of them are watching TV while they actually have another device next to them, a laptop or maybe an iPhone.
Thus, factor in that people come to your website from different channels. Using the Multi-channel Funnel, in this case, to report on that kind of activity holds relevance. And to help you with that and if you are thinking about your plans for next year, you can leverage what Google has announced and labeled as Universal Analytics. It’s a new generation of Google Analytics that is very user-centric. It allows you to track user behavior across several devices and also across different touch-points described earlier.