Separate visits that include your login area from the rest with a segment, or mark clients when they log in. Then judge newcomers on arrivals and enquiries, and clients on whether they find what they came for.

Healthy visits, few enquiries

An accounting office reads its monthly report. Visits are steady and look healthy, yet enquiries from new people are few, and the rate of enquiries per visit looks poor.

The partners wonder whether the site attracts the wrong people, or whether the enquiry form has stopped working. Then someone notices that the second most viewed page, after the home page, is the client login.

A good share of those healthy visits were never prospects at all. They were clients, arriving to upload documents.

Two audiences in one report

Existing clients come to log in, download a statement or check a price list. They never fill in the enquiry form, because they already have a relationship with you.

Yet each of their visits counts in the total that the enquiry rate is divided by. The more often clients log in, the worse the site seems to convert, though nothing about it has changed.

They also fill out the visit count, which hides the more useful number: how few new people arrive in a month, and from where.

Signs the clients are in your numbers

A few patterns in the standard reports point to a large client presence:

The last usually means the area behind the login carries no tracking code. Every client who signs in successfully then looks, to Analytics, like someone who saw one page and left.

Returning is not the same as client

Analytics already splits visitors into new and returning, and it is tempting to read returning as clients. The split rests on a cookie in the browser, not on who the person is.

A prospect taking a second look is returning. A client on a new office computer, or one who clears cookies, is new. The split blurs exactly the line you want to draw.

Separating them with a segment

A segment limits a report to the visits that meet a condition. Build one for visits that include a page in the login area, and a second for visits that do not.

Apply both, and every standard report shows the two groups side by side: sources, pages, devices and goals. The enquiry rate for the second group is the one that describes your marketing.

Segments work on past data too, so last year's figures can be split the same way without waiting for new visits.

Marking clients once they log in

A segment based on pages misses the client who visits only to find your phone number. A sturdier mark is set by the site itself when a login succeeds.

A small change to the code on the page after login records the visitor as a client, using a custom variable in the classic code or a custom dimension in Universal Analytics. Later visits from that browser carry the label.

Record the type of visitor only, never a name, an email address or an account number. Google's terms forbid sending personally identifying information to Analytics.

Goals that match each group

A goal in Analytics records a visit that reached a chosen page, such as the thank-you page after the enquiry form. Most small sites have one goal, if any, and it suits only newcomers.

Add a goal for the clients' purpose as well: the page after a successful login, or the price list download recorded as an event.

With both goals set, each segment shows its own completion rate. Newcomers who never reach the thank-you page and clients who never reach the download are two different problems with two different fixes.

A worked example

A seed company on the Saanich Peninsula sells to home gardeners through an online catalogue, and to garden centres and market growers through a trade area where they log in for wholesale prices.

Its report showed steady visits and a low rate of catalogue requests and trade applications, and the owner suspected the site was drawing casual browsers.

The trade login was the second most viewed page, and visits rose each fall when the wholesale list came out. The trade area had no tracking code, so every order there looked like a bounce.

The tracking code went into the trade area, and a custom dimension now marks a browser as trade once its owner logs in. Two segments, trade and everyone else, sit on the main reports.

The catalogue requests are now divided by visits from potential customers only, and the trade figures show whether garden centres find the price list. Each number answers its own question.

Judging each group on its own terms

New visitors are judged on arrival and interest: how many come, from which sources, which pages they read, and how many enquire. Those are the numbers marketing changes.

Clients are judged on service: whether logins succeed, whether the downloads are found, and how often the password reset page is used. More client visits can simply mean clients rely on the site.

Report the two groups separately from now on, so nobody compares a blended rate with a newcomers-only rate and sees a change that is not there.

The counter-case

For some businesses the logged-in customers are the point. A supplier whose dealers order online wants that group to grow, and its numbers matter more than the newcomers'.

And where clients log in on a separate system on another domain, they may barely appear in the main reports.

In both cases the split still earns its place. Each group is measured against its own purpose, instead of one blended rate that describes nobody.

Splitting the report

  1. Check the top pages for the login and client area.
  2. Confirm tracking code runs behind the login.
  3. Build a segment for visits that include the client area.
  4. Build its opposite for everyone else.
  5. Mark clients with a label set at login.
  6. Set separate measures for each group.
  7. Keep an unfiltered view as the untouched record.

Step four gives the honest enquiry rate. Divided only by visits from people who might become clients, it shows what the site does for new business, which is what marketing decisions need.

Trying a new filter on a separate view before trusting it, with bots as the case in point, is covered in filtering known bots out of Analytics.

Frequently asked questions

Why do client logins lower the enquiry rate?

Every client visit counts in the total the enquiry rate is divided by, though clients never enquire. Frequent logins make the site look worse at converting than it is.

Can I use new and returning visitors instead?

Not reliably. That split rests on a browser cookie, so a prospect's second look counts as returning and a client on a new computer counts as new.

What is a segment in Google Analytics?

A condition that limits reports to matching visits, such as visits that include a page in the login area. Segments also apply to past data.

Why does the login page have a high bounce rate?

Usually because the area behind the login has no tracking code, so a client who signs in successfully looks like someone who viewed one page and left.

Can Analytics record which client visited?

It should not. Google's terms forbid sending names, email addresses or other personally identifying information. Record only the type of visitor, such as client or trade.

What should client visits be judged on?

Service: whether logins succeed, whether downloads and price lists are found, and how often people need the password reset page. Frequent visits can simply mean reliance.

West Coast Media Solutions Inc. provides web design, web development, hosting, digital marketing, and business consulting to organisations across Canada, drawing on more than twenty-five years in the field.

Client logins mixed into your visit numbers?

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