When people think of conversions, they usually think of sales. And that's good - sales are good. Depending on the industry though, sales can range from .3 percent to 3 percent of the visits to a site. Even using the optimistic scenario of 3 percent, it is not healthy behavior to think a company is failing the other 97 percent of the time.
Some of an enterprise's "non-converters" might be converting quite a bit - they are consuming educational pages, they are clicking through pay-per-click (PPC) ads and remembering the brand, they are signing up for a mailing list and, overall, they are doing things that drive them closer to a sale. And some of them are not.
Marketers need to know who is who - even if the data is not neatly stored in one place.
Pay Per Click
Many advertisers use AdWords for "direct" conversions. Even when a direct conversion is not received, however, it is still possible to get people closer to the sale:
+ Get people to download a document with a CTA that leads them down the funnel.
+ Get the brand exposed enough to get the sale later.
For that to happen, marketers need to pay close attention to both the stats in AdWords itself, as well as the stats passed from AdWords into tools like Google Analytics. Enterprises can view the click-throughs and costs within AdWords, and the total cost and on-page behavior within Google Analytics.
If marketers are keen on tracking PPC behavior and saving the company some money, they can compute more advanced things. They can compute which ads have the lowest cost for engaged users, lowest cost for people who download key collaterals and so on.
To carry out this critical step, however, a brand's AdWords account needs to be tied pretty closely to its Web analytics tool. For Google Analytics (GA), specifically, this is a tie that can be made by the company's rep and approved by the owner of its GA account.
This is also one of those areas where if a company has a business intelligence (BI) tool like Tableau, and a good way to sync data, it might be easier to run some of the computed values like average cost for people who download a piece of collateral.
Do not stop with just direct "sales" conversions. There are a handful of small battles to win before marketers win the war.
Even if people don't buy something from an enterprise, if they provide their real email address, they are giving the company some level of permission to contact them. That is a win - every email that is stored by getting people something (a whitepaper, a software trial) - is a win.
If brands contact them blindly for campaigns that are not related to what they signed up with, they will be wins that have resulted in nothing, though.
Therefore, marketers need to understand the data that lives in their marketing automation software. Marketers need to do not just do raw counts of emails stored, they also need to:
+ Track campaigns people are a part of.
+ Understand who the hot leads are and what their criteria is for people to make it to those lists.
+ Know the open rates for campaigns.
+ "Tag" the emails they are sending out with enough details so that Web analytics data can pick up what happens to the user the rest of the way.
A lot of that is not easy to do accurately. The line-by-line contact data on marketing automation tools does not usually easily gel with pre-computed data on Web analytics tools.
That said, wherever data comes from and however it is stored, marketers need all of the data to tell one coherent story. That is the only way marketers will be able to prioritize which areas to improve.
Customer Relationship Management
A lot of the time, the contacts data used by the marketing automation system also get used by the customer relationship management (CRM) system. Whereas the marketing automation system is responsible for the email campaigns and lead scoring, the CRM is usually the thing responsible for tying contacts into actual sales.
From here, marketers need to understand how many leads end up being qualified leads, and how many qualified leads eventually become sales. It would be a shame if all the early stage funnel work turned out great, only for marketers to stop optimizing at the end of the funnel.
10 Checkout Page Strategies Consider these time-tested strategies to turn more carts into conversions at wsm.co/tencheckout.
Yes, Web analytics data can store the value per sale, and give marketers a value per page, and give them a direct conversion rate.
There are thousands of references of the Web that help marketers obsess with the 0.3 percent or the 3 percent of people who directly buy from them. Web analytics data carries so much more than that, however, and if marketers focus on their effort on the 3 percent to the exclusion of everything else, they will be playing for a smaller and smaller market. Marketers need to understand...
+ The growth and reach of educational pages for the top of the funnel. Marketers should treat organic growth for educational pages as a small conversion - its health can help determine the number of conversions enterprises have down the pipe.
+ The bounce rate of pages where marketers lead emails and PPC ads to, even if they don't result to a sale on that visit. Marketers can treat the non-bounce visits as small conversions as well.
+ The downloads of key collateral material, which can constitute middle of the funnel success.
There are a ton of things to improve before potential customers buy from an enterprise. A Web analytics tool houses a ton of the data that can be used to course correct the site when it comes to top and middle-of-the-funnel visitors.
Consuming the Data
For campaigns, if marketers have the organizational sophistication for it, business intelligence tools can help, especially with two kinds of reports: + Tying together one campaign - if marketers have one campaign that takes data from their analytics tool, the contacts database, the system being using to track leads, etc., it would be great to set up a campaign report that has some minor filtering/organization capabilities. + Generic dashboard data - it saves time if the basic site health data can be run via BI tools.
That said, a lot of the time, marketers will want to handle the individual tools, segment/filter data from there and hunt for insights themselves.
About the Author Martin Greif brings 25-plus years of sales and marketing experience to
SiteTuners where he is responsible for driving revenue growth, establishing and nurturing partner relationships and creating value for its broad customer base.
Martin is the President of SiteTurners.com, a company that helps businesses overcome growth challenges. Clients turn to SiteTurners when they face increased acquisition costs, stagnant revenue and conversion rates, and difficulties scaling their operations. With a focus on testing and marketing funnel optimization, Martin and his team aim to help businesses generate more sales, leads, and subscriptions and achieve their desired growth.