Getting the most from your Digital Marketing dollars is the theme of our September webinar, and based on the turnout, this proved to be a popular topic.
We were joined by two subject matter experts in the field: Tom Patryshen, founder of the Data Collective, and Mike Giles, Digital Marketing Specialist from Graphically Speaking.
Here are some insights that Tom and Mike shared with us during the webinar:
Part 1: How to Improve Your Google Analytics Data Quality
Presenter: Tom Petryshen - Founder at Data Collective - firstname.lastname@example.org
Tom Patryshen's talk focused on data and data sources, which for most organizations will reside in spreadsheets and Google analytics.
To get the most out of your data, it needs to be clean. That begins with web developers producing error-free code. Your website's forms, UX and UI elements will be collected and analyzed, and that data from those sources needs to be clean so you can know what's working or what's not working on your website.
One of the difficulties with today's online environment stems from the shear variety of data sources that contain your visitors' data. This makes it hard to identify and market to your contacts. However, there are excellent tools like Segment that are available to help you connect, clean, and sort your data so you can build targeted personalized marketing campaigns.
Google Analytics is a great tool to start collecting and aggregating your website data, but only when your data is clean can you trust it to help you make informed marketing decisions for your campaigns.
Here are some tips Tom shared that you can use to normalize your data:
Segregate mobile and desktop metrics.
It seems fundamental, but be sure your data starts with a clear division between mobile and desktop metrics.
Tagging - fix the issue at the source
To understand how your campaigns are working, it's essential to tag your sources. With Google's campaign URL builder, you can create tags that will filter traffic by source so you can analyze and manage your campaigns. For example, differentiating paid social data from regular social results. Otherwise, you'll end up with a non-descript bucket of data that won't give you insights.
Clean the data with business intelligence tools
You can also set up filters and aggregate unrelated data sources using BI tools like Power BI, Google Data studio, etc., but the best way to do this is to fix data issues at the source.
Update organic search by applying filters in Google Analytics
It is also important to update and organize your organic search sources in Google. You can do this by going into Google's Admin > Tracking Info > Organic Search Sources to add in search engines that Google isn't picking up (e.g. Yahoo, Bing, Duck Duck Go, Yandex, Baidu, and more). Google will then funnel your traffic into the related organic search baskets.
Exclude internal traffic
Website's traffic data can be muddied by visits that originate from inside the organization. This can skew bounce rates, pages per session rates, conversion rates, and more.
Account for font case variants
If something is described using lower case and upper case, Google will treat that as separate data entities. For example, Google sees "red dress" differently from "Red Dress" or "Red dress" so you'd end up with 3 different instances of red dress within your data.
By going to Admin > View > Filters, you can set filters for campaign names, sources, media, content and page paths to ensure your data is consistent in Google Analytics.
Combine disparate source data
Traffic from social channels can originate from multiple URL sources (e.g. m.facebook.com, I.facebook.com, facebook.com, business.facebook.com, Im.fcebook.com). You'll want to combine these into a single manageable domain source, otherwise Google will see them as individual sources.
Block bots and spiders
Simply go into Admin > View > View Settings and click the text box to ensure that your excluding bots from messing with your data.
Block crawler spam
There's no shortage of crawler spam on the web and you'll want to block it. Tom provided a useful reference and link to Carlos Escalera's website. The site offers lots of analytics resources, including an updated crawler spam filter pattern list that you can apply to your analytics filter.
Exclude ISP providers
ISP crawlers can also crawl your site and create additional rows of data that will skew your analytics results. Carlos Escalera includes lists of crawler filter patterns that you can use to filter ISP provider bots.
Exclude Query Parameters
If you have a dynamic website with a lot of perimeters, Google will take each different perimeter and treat it as a different URL. This means you won't be able to see collated traffic for a single page. Instead, you end up with dozens of variations of a page within Google's top landing page report.
Include your Host name
You'll also want to stop ghost spam from infecting your data by creating a filter for your host name. This will exclude all data that might be assigned to a different domain name.
Watch your language
Language variants can disguise your data and negatively impact your campaigns. They should be removed from Google Analytics using the filter Admin > View > Filters > and placing the following filter pattern into the Filter Pattern field:
Eliminate fake referral Spam
Spammers with the goal to take you to their websites will inject spam into your analytics. Again, you can remove fake referral spam and clean up your data by introducing a filter pattern.
Remove duplicate transactions
When data is written into a Google table it stays there permanently, so with ecommerce websites where visitors may visit a transaction page several times over multiple sessions, this will create a problem and cause your transaction numbers to go up for the same ID and skew your data. You can mitigate this by creating a report in the custom report in Google Analytics that combines transaction IDs with transactions. You can also deal with it by creating a custom tag variable within Google Tag Manager to filter out the data.
Filter after the fact
Now that your filters are set and you're getting clean data, what if you want to compare data from before the time before you set up those filters? Well, you can filter out the old dirty data in Google Analytics. You can create filters within the segment portion of Google Analytics, and you can apply the filters that you previously set up in Google's admin section to the segments that you're dealing with now. The lets you designate a section for users' clean data, which essentially allows you to clear out all the old dirty data.
One of the difficulties with today's online environment stems from the shear variety of data sources that contain your visitors' data. This makes it hard to identify and market to your contacts. However, there are web-analytics consulting services and excellent tools like Segment that are available to help you connect, clean, and sort your data so you can build personalized marketing campaigns and ultimately enhance your marketing success.
Part 2: How to Measure the ROI Of SEO
Presenter: Mike Giles - Digital Marketing Specialist at Graphically Speaking - email@example.com.
Mike Giles of Graphically Speaking went into detail on measuring and calculating the return on the investment of SEO.
The SEO ROI Formula
Given the expense to attain optimal organic search rankings, and the fact that, unlike Paid Ads, the metrics for SEO are intangible, SEO results can be difficult to understand, control or measure. The following formula can help calculate ROI.
SEO ROI is a calculation that measures the return on investment of search engine optimization by looking at search engine rankings, organic website traffic, and goal completions, using the ROI SEO formula:
(Gain from Investment - Cost of Investment)/ Cost of Investment
It's best to start this work early, as tagging and tracking conversions will give you data that can help you to make informed decisions regarding your marketing campaigns, UX design and other website features. We recommend using Google Tag Manager to set up conversion tracking, starting with a single snippet of code.
Calculating SEO ROI begins with adding conversion tracking tags to your site so when someone completes an action you can assign a value to an action that you've defined as valuable. Downloading a newsletter or a content offer, submitting a quote request, clicking a phone number or buy button are all valuable conversions.
The website's purpose will dictate the conversion tracking goals. The goals for a brochure site will differ from those of an ecommerce or lead generation website where monetary transactions, form submissions, and inbound calls will be measured.
Common goals for lead-based businesses will include form submissions, requests for quotes, and phone calls. Segregating forms (e.g. contact and quote forms) will ensure that your data will be clean and manageable. A "thank you" page is a great way to gauge these conversions, as the page can only be generated after a form has been submitted from a specific page. This also gives you the opportunity to do some follow up marketing to prospective customers.
For ecommerce websites, ROI is calculated as revenue generated by a campaign over time. This might be measured over 30, 60, 90 days, quarterly, or longer. By looking at how your channels are producing revenue, you can shift dollars away from low performing channels to higher performing ones.
Formulas for determining lead value and ROI:
For Lead Generation websites:
Determine how many leads convert to sales, then determine the average value of each sale, which will give you the value of each lead.
- of 100 leads per month, 25 become clients = a 25% conversion rate.
- each customer spends $200 = the average customer value is $200.
Now divide the total value of conversions by the number of leads:
- 25 customers x $200 = $5,000. And $5,000 / 100 leads = $50 (the value of your leads in this case is $50.00)
For Ecommerce websites:
The ROI for ecommerce websites can be calculated as revenue generated by a campaign over time, this might be measured over 30, 60, 90 days, quarterly, or longer.
ROI formula for ecommerce:
- gain from investment = $600,000
- cost of your SEO $125,000
- (600,000 - 125,000) / 125,000 = 3.8 *100 or %380!
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