The most important aspect of web analytics is being able to utilize the information you collect to create strategic and actionable next steps for your company. As your firm’s analytics expert, the best way you can help do that is by creating specific reports for the various departments throughout your organization that focus on their key goals.
The sales team is solely focused on how the website can generate revenue or bring in new sales leads. You can help them improve their current strategies by providing insight on how the website and other marketing tactics contribute to purchases and lead generation. Depending on whether your website is B2C- or B2B-oriented, you’ll want to structure your report for the sales team differently.
Business to Consumer
If you’re working with the sales team at a B2C company, they’re responsible for increasing the purchases on an ecommerce site. They’re going to be interested in the retailer’s overall revenue and ensuring that it is increasing over time. Equally important to them, however, will be the flow of traffic to the website and whether or not your company’s marketing tactics are attracting the types of visitors that are likely to make purchases.
So, when compiling an analytics report for a B2C sales team, you’ll want to include data about both traffic and revenue. A good place to start is the Google Analytics Channels report (Acquisition > Channels). This report breaks down traffic stats by acquisition channel and will help the sales team understand how visitors find the website and where the most engaged customers come from.
In the example above, you’ll want to call out that Referrals bring less total sessions but that they’re more engaged – they’re spending more time on the site (higher Avg Session Duration) and visiting more pages (higher Pages/Session) than those driven from Direct or Social. Based on this information, the sales leadership may decide that more time and money should be spent on affiliate marketing, content marketing, link building, and other types of campaigns that generate referral traffic.
Be aware that engagement metrics like Avg Session Duration can be skewed by website design and audience behavior. For details, see the Appendix.
With a slight change, you can make this report break down the revenue by channel. At the top of the report (under the Explorer tab), click on the link labeled Ecommerce.
In order for this report to produce data, you’ll need to have Ecommerce set up in Google Analytics. For help with that step, you can read this article on setting up Ecommece tracking.
When presenting this data, show the sales team how certain online channels are driving sales. This will help them understand how well promotional efforts, like email campaigns and coupons, are working. In particular, look at the Ecommerce Conversion Rate and Per Session Value to determine which channels bring in the most qualified traffic. The sales team can review this report and determine how to adjust campaigns to encourage more sales. For example, in the above report you can see that the Organic Search and Direct channels are driving the most transactions. However, Email has the highest Ecommerce Conversion Rate and second highest Per Session Value. Based on that information, the sales leadership might like to see more resources allocated to email marketing.
The Location report (Audience > Geo > Location) provides your sales team with insight into which geographic regions they should dedicate their resources. As with the Channels report, click the Ecommerce option at the top of the report to see the areas that bring in the most revenue. The sales conversions will give you an idea of where you should be targeting your campaigns. On the other hand, you may want to promote more heavily in the geographic regions that need to improve sales performance.
Note that the Geographic data in Google Analytics can be inaccurate for some audiences. See the Appendix for details.
Sometimes, the standard reports offered by Google Analytics cannot provide all the information you need to pull together for the sales team. For such situations, it helps to have mastered the art of creating Google Analytics Custom Reports. There are plenty of tutorials on the web, and this Econsultancy blog post is a good place to start.
Custom Reports helped me out in one B2C consulting project that I was involved with recently. The company was a start-up children’s clothing retailer selling strictly over the web to customers in the United States. They had a limited AdWords budget and they were trying to increase sales without spending more on ads. I created a simple custom report showing Ecommerce revenue by hour of day. Here is a link to my report, so you can try it with your own data.
The data showed a spike in purchases happening between 11:00 – 12:00. From this, we assumed that people were most actively searching for (as well as buying) during that period. The company decided to shift more of their AdWords budget into those hours of the day. Although this decreased results in the latter half of the day, the increase in the morning more than compensated, and overall revenue increased by 5%.
Business to Business
A B2B sales team will want to look at the same reports discussed above, but in addition, they’ll want to track goal conversions. In particular, goal conversions that measure the number of sales prospects coming from the website. Website visitors turn in to prospects by completing certain actions on the website, such as requesting more information via a form, signing up for a demo, or subscribing to a mailing list. Each of these actions is a goal completion that can be tracked in Google Analytics. To learn how to do this, follow these instructions.
The potential clients who are taking these first steps in the sales process are likely to be those who convert to customers later in the sales funnel. Show the sales team which channels are contributing the most leads by using the Channels report (Acquisition > Channels) and selecting an appropriate goal for the last 3 columns, using the Conversions selector.
From this report the sales team can identify channels that are working well and might benefit from additional investment. In this example, Display advertising is showing the second best conversion rate at 0.21%, but relatively low traffic volume compared with other channels. Based on this information, the sales leadership may decide that more marketing dollars should be allocated to Display ads.
Similarly, you can show the Sales team the Location report (Audience > Geo > Location) configured for goals, so that they can see what geographic regions are producing the most prospects.
Since B2B sales teams often structure their efforts according to sales territories, this information will help them determine what regions their resources should be allocated to in order to convert prospects into sales most effectively. Regions that show up as light on conversions may prompt the sales team to dedicate more lead generation campaigns in those territories. In this example, you can see that the New York and London areas are generating a lot of leads. By comparison, the large population centers on the West Coast of the United States are not generating as many. Perhaps the California marketing efforts need to be increased to better support the sales team covering that territory.
Conclusion
The sales team either directs or strongly influences how digital marketing resources are allocated. You can help them make the best decisions possible by providing reports that show which channels and campaigns are bringing the right types of visitors to the website. The quality of the traffic being delivered can be measured in terms of engagement, goal conversion, and online revenue. B2C sales teams are likely most interested in engagement and online revenue. B2B sales teams care about these metrics too, but are also interested in goal conversion because that’s how they measure the volume of prospects being generated.
The Google Analytics reports outlined in this post provides you with a starting point to create the specific reports that will be most valuable to your sales team. They’ll appreciate the data and work with you to fine tune the reports so that they can provide the most benefit to the organization overall.
Appendix
About Engagement Metrics
Engagement metrics – Bounce Rate, Pages / Session, and Avg Session Duration – can be misleading if used to compare your website with other websites. That’s because a number of factors specific to your site and audience can skew these metrics. For example, Google Analytics counts any one page visit as a Bounce, except when the visitor takes some action on the page that fires an Event. So, the Google Analytics tracking on your landing page can actually skew the Bounce Rate down. I have seen cases where the website opens a “Subscribe Now” or similar lightbox that is tracked using an Event, and the Bounce Rate is driven practically to zero. In another example, Avg Session Duration can be affected by tabbed browsing behavior. Users may open a link to your site in a new browser tab, and not start looking at it for several minutes. Once they start looking at your page, and navigating your site, that idle time will be counted by Google Analytic as time spend on your site (unless the idle time exceeded 30 minutes, in which case when they come back, Google Analytics starts a new session). The idle time that gets counted as session time can artificially inflate your Avg Session Duration. So, if your audience contains a high percentage of power-browsers who open a lot of tabs, this metric can be impacted.
For these reasons, it is best to use engagement metrics to evaluate relative behavior on your site – rather than as a method for comparing with other sites. For example, look at how the Bounce Rate for your site varies across Channels to compare the relative engagement of traffic from different sources. Your data may be skewed, but it is probably all skewed in the same direction, so you are safe comparing within your own site.
Return to Engagement Metrics
About Geographic Data
Geographic data can be skewed by virtual private networks (VPNs) or proxy services. That is because Google Analytics calculates a visitor’s geographic location using their IP address. Visitor using a VPN or proxy often have an external IP address in a different location than where they are physically present – sometimes even a different country. This is particularly common in countries where governments restrict Internet access. For example, a visitor from Beijing using a proxy to avoid government censors may be routing their traffic through a server in California. That visitor is going to show up as coming from the USA, not China, in your Google Analytics reports.
Return to Geographical Location
Alex Brooke says
November 12, 2014 at 1:42 amHi,
Firstly what a great article! Your raise some very interesting points. I think you raise a great point for b2c businesses particularly by looking at the revenue by hour.
What I’d also say is that it’s vital that when your analysing these kind of campaigns, you need to look at the revenue by day. What I mean by this is that you might find that products (or services) could sell more on a Monday as opposed to a Saturday so breaking down where this occurs can be vital to ensure your marketing spend and efforts are used wisely. You could also find (as we have with some of our clients’ Adwords accounts) is that weekend days such as Saturday and Sunday can sometimes be more competitive in terms of cost per click.
The part you mention about the engagement metrics at the end of this article I feel cannot be preached enough! I’ve looked at many analytics accounts and found that bounce rate, page views and even number of sessions can be skewed by many factors.
My top tip would be that if you see unusual statistics within your analytics account, before you create your report for your client or yourself, check your Google analytics code is working properly. You can do this by using the Google Tag Assistant which is very helpful in determining whether your code is installed properly. Also check your website source code and take a look to see if your code is entered correctly. You don’t have to be an expert with this I’d just say look out for things such as duplicate analytics tracking codes – we recently found this with a client who had said that their bounce rate was at 93% and due to incorrect implementation of the Google tracking, the analytics was registering some inconsistencies.
After spending many previous hours on the phone with Google discussing analytics issues I’d also say check that the real time tab is working correctly as this can also be a good indication that your code is firing incorrectly.
Another factor to bear in mind is that when Google automatically updated all old analytics accounts to Universal Analytics, the tracking code which is already in your website source code could prove to be deprecated causing you to see some unusual analytics results.
And on a final note I’d also say that whether you’re an e-commerce business or a b2b business, if your employees are regularly using your website, I’d certainly recommend filtering out your company IP address and including this within a separate analytics view. This is because employees should know where products and information can be found on your website so it’s likely they will not follow the same visitor path of the consumer. Also it’s probably likely that employees will be using your company website to verify information. In this case they may only need to look at one page and then leave – which will affect your bounce rate if you do not filter it.
Thanks for taking the time to write this article. I’ll look forward to reading more in the future.
Mark Hansen says
November 12, 2014 at 10:47 amHi Alex,
Glad you liked the article!
All your points are valid and useful advice, but particularly the importance of looking at revenue by day. Depending on the business, interest and demand is usually a lot stronger on some days of the week than others. Optimizing AdWords bids and budgets to advertise more aggressively on those days can have a big impact on ROAS (return on AdWords spend).
I also liked your notes on the importance of good analytics hygiene – something I didn’t really address in the article. Checking the tracking code, filtering out internal visits, etc – all are vitally important for ensuring the numbers in our reports are accurate.
— Mark