For those of us in charge of ad spend, we know there’s a lot of data to dig through - Google Adwords, DoubleClick, Facebook, LinkedIn, Bing, TubeMogul, Brightroll, etc. At any given time, you have dozens of ad campaigns running, all of which generate hundreds of thousands of events left to be analyzed and ROI to be proven.
Trying to make sense of all your data and attribute every channel’s impact to your marketing funnel can seem like an impossible task.
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What’s next?
5. The days of posting a sign and waiting for customers to knock on
your door are all but over. Today’s marketing success is built on
insightful, actionable data – even for offline channels like direct mail,
print and radio.
Marketing Data: What’s Possible, and Why it Matters
Successful marketers are
leveraging their ad spend to learn
how & where to spend their next
dollar.
6. Clean Data: Getting-Out What You Put-In
Well targeted ads can easily track:
•Demographics: age, gender, marital status, etc
•Psychographics: interests, political views, social preferences
•User-Behaviors: shopping habits, subscriptions, recreational habits
•Geography: IP address, zip codes, city/state or “local area” using radii around a business location
•Messaging: promotions, discounts, sales, and the imagery & verbiage that drive results
The Trick: Label your ads according to who they target, put tracking info into the
‘destination URL’ of every ad and make sure you’ve got a web analytics platform
that can capture that info, along with valuable website activities.
7. Getting Results: Define & Prioritize Your Goals
Typical Goals:
•Reach & Awareness – focus on unique reach & frequency
•Drive Interaction – focus on interactions and CTR
•Maximize Site Traffic - focus on CPC
•Maximize Conversions or Sales – focus on CPA and Conversion Rate
•Maximize ROI – focus on CPA, Revenue per Click, and Revenue per Conversion
Consideration can be given to multiple goals, but one must take priority. Whatever your primary
goal, make sure you have a way to monitor the appropriate metrics and map any “success
event” back to the specific ad that drove that event.
8. Doing more of what works best, and less of what doesn’t is
very intuitive in theory. In practice, it means complexity, attention
to detail and a keen eye on statistical significance. It’s not easy,
but it’s always worth doing.
Follow the Data, It Doesn’t Lie.
9. With the sophisticated campaigns you can run, all the data that you
can collect from digital marketing efforts on Google, Facebook, etc. it’s
easy to get buried and lose sight of the business value and data driven
decision making abilities.
Dashboards for Actionable Business Value
Digital Marketing Scenario:
10. Business Value Design Best Practices
• Back to basics: Analytics deliver value by enabling better
decisions
• Tie metrics to the business reasons, business problems that
need solving
o Tie to the business strategy with a visual context
o Analysis path to what people in a role need to make a business
decision
11. Digital Marketing Dashboards Best Practices
Compared to more traditional ‘Business System’
based BI:
•Challenge is LESS of going to various business
systems to acquire and integrate data
•Challenge is MORE of filtering out all the data that is
not relevant to your specific business focus
Best Practice: Minimize the noise, focus on presenting the metrics
with their context related to your defined business problem.
Swimming through all the data is a Data Scientist exercise!
12. Digital Mouth Dashboards
Business Decision Starting Points: (root of path through
the data to get to decision points)
What's happening right now, is it on track? (mechanically getting
the impressions in the right place at the right cost)
Analyzing inside the campaign to answer:
'What did I say‘
'Where did I say it‘
'Who did I say it to'
It’s possible to track phone call volume, website visits & activity, sales, in-store visits, coupon redemptions and just about anything related to “success” stemming from a marketing campaign.
Every dollar spent should be done with the goal of evaluating “winning” and “losing” tactics. Opinions and assumptions are often detrimental – statistically valid data can & will guide you to success if you track appropriately, carefully test specific variables and use the results to guide future ad spend.
For most marketers, granular data requires granular segmentation of your ad placements. You can’t simply target “everyone” and get the insights you want; by targeting ads to specific segments, tracking (and testing) those segments becomes feasible at any budget level.
CRUCIAL here is making sure you have “end to end” tracking from ad impression to end-result (sale, conversion, enrollment, etc). Example: 4 promotions, 4 ad sizes, 4 age groups (18-25, 26-35, 36-55 and 55+), 2 genders, 50 states = 6,400 Individual Ads.
Google Analytics UTM parameters are the easiest way to pass tracking from an ad to your site, letting you associate all website visits and site activity to the SPECIFIC ad that drove the activity. With that, you have a clear view from ad impression, through clicks and site visits, to Revenue and ROI.
Where this becomes difficult is tracking thousands of placements and target segments. To do that, you need to move beyond text-based URL parameters and use some sort of ID.
Most brand managers would tell you that they want to reach as many people as possible, drive as much interaction as possible to maximize site traffic and deliver the best conversion rates and ROI. While those are all reasonable goals independently, it’s impossible to deliver all of those things at once.
I’ll give you a few examples:
In maximizing reach, we’re reaching more and more of the people who are less and less likely to interact or convert. This helps us increase awareness, but it also means lower CTRs and less interaction per dollar spent.
With respect to maximizing CTRs and website traffic, the best example I’ve personally seen is the use of “bad credit ok” in ads for mortgage services. This phrase alone can increase CTRs and generate more website traffic, but it’s traffic that simply doesn’t make a mortgage company money in return.
In maximizing conversion rates or sales volume, you might strive for the opposite of the “bad credit ok” tactic. In the case of a mortgage company, it’s reasonable to assume that driving consumers with high income and good credit to your site is a good thing – but this doesn’t speak to the cost of that traffic. You’ll often find that the best quality traffic is simply too expensive, and doesn’t lend to the best ROI.
It’s possible to track phone call volume, website visits & activity, sales, in-store visits, coupon redemptions and just about anything related to “success” stemming from a marketing campaign.
Every dollar spent should be done with the goal of evaluating “winning” and “losing” tactics. Opinions and assumptions are often detrimental – statistically valid data can & will guide you to success if you track appropriately, carefully test specific variables and use the results to guide future ad spend.
Focus on specific, iterative tests. You can’t learn everything at once, and you don’t need to – if your goal is to maximize site traffic from your ads, consider starting with tests around the images or promotions in your ads. If your goal is to improve website conversion rates, consider testing landing pages or conversion funnels to find a conversion path that maximizes your conversion rates or better yet, revenue per site visit.
Identifying your goals will let you identify your best opportunities to test and improve your campaigns.
for example: 2 takes on showing Quarterly Sales Revenue KPIs.
1)emerging market company, all focus on making the #.
2)public company, needs to balance making the # with how they make the #