Is Your Paid Search Campaign Part of a Mix or a Mess?

Incorporating your client's media plan into your paid search campaign can help you decide whether to raise or increase budgets and bids. However, studying the relationship between “other media” and paid search campaigns can sometimes lead to counter-intuitive findings.

No hard and fast rules exist that say “Raise your budgets if X," or "Decrease your bids if Y.” Each campaign must be studied independently to discover the underlying patterns. That effort can be a) easy as pie, or b) agonizing torture. So, which will it be?

To answer that question, I've put together a little questionnaire to help figure out your MESS (Media Energizing Search Score). In my experience, your MESS depends on many different factors (please choose the answer that most closely represents your situation):

A. How many types of “other media” (TV, radio, direct mail, online display, etc.) do you run?
1. Just a few other media, like online display and direct mail.
2. Several different types of media (radio, newspaper, direct mail, and online display)
3. Name it, we do it.
4. No other media besides paid search (which complements our organic results).

B. Do the media turn on/off (pulse) over time, or it is a consistent (trickle or barrage) over time?
1. Pulse is an under-statement; there is no consistency over time.
2. Anyone with Excel could predict our next move. Heavy-up the week before holidays, then do a quarterly customer retention campaign.
3. Our media efforts are constant. "Stay in front of the customer" is our motto.
4. We really don't do any other media activities.

C. Is your historic media activity shown at the day, week, month, quarter level?
1. Day of week
2. Week
3. Month
4. Quarter

D. How much historical media and search data do you have?
1. Several years
2. About one year
3. Less than one year
4. None

E. To what extent does your company do geo-targeted, experimental media tests of the media mix?
1. We have test markets we use to test our media channels before roll-out.
2. We test media channels by looking at before-and-after differences.
3. It's a foregone conclusion; we know which media work, and which do not.
4. Experimental media test? How?

F. Are you trying to squeeze another 5 or 10 percent of efficiency out of your search efforts? Or do you suspect there are large efficiencies remaining to be exploited using ad copy and landing page tests, as well as elementary budgeting optimization?
1. Running paid search campaigns has been a constant struggle; we depend on the search engines to give us good advice.
2. We're not bad, but we could probably use more detailed analysis/testing/optimization in order to improve our paid campaigns.
3. Our paid search efforts are pretty good, but we occasionally find ways to get to the “next level.”
4. Our paid search campaigns are quite sophisticated; you can't get blood from a turnip.

G. Do you have dedicated teams of analysts with a background in forecasting and predictive modeling?
1. Our search campaign manager is the analyst.
2. There are statistical analysts available, but I don't know their names. Who do they report to?
3. We have one or two people dedicated to producing reports and analyzing our search data, but they are not statisticians.
4. Our super hero statistical analyst is currently building predictive models and forecasts for the paid search team.

H. To what extent does your manager want results NOW, as opposed to supporting long-term projects with no immediate payoff?
1. We live and breathe numbers, and rarely take major actions without analytical support.
2. Our statistical group has been looking at media effects for the past 3 years. Their findings should be ready sometime in the distant future.
3. It's important to think about long-term improvements, as soon as I can get through the next few months of web design changes, the new web tracking installation, holiday season, and training of your new team member.
4. I really shouldn't be reading this article, because the CEO recently searched for a term and did not see any ad from your campaign.

I. Do upcoming media plans change so much that it's like a constant fire-drill of last minute cancellations and updated insertion orders in the media buying department?
1. Plans are plans, and budgets and budgets. They were signed off on 3 months ago.
2. Heh, what's this? A change order to our quarterly plan?
3. There's always a certain amount of media plan updating in the month before launch.
4. Run! I just got another email from the EVP of Marketing shifting the media budgets.

J. Is your marketing coordination agnostic about the channel (online, offline) of conversion, as long as it's the most efficient as possible?
1. Analyses of our media mix show the optimal allocation of spending across channels, regardless of the conversion channel.
2. We are keenly aware that marketing in one channel produces conversions in another channel. But we have a hard time measuring it.
3. The EVP of Marketing recently read that more money is moving toward online and search; my budget is going up!
4. I've got my numbers; they've got theirs. It's a zero sum game in the corporate world.

What Kind of MESS Are You In?

Okay. Now let's add up your answers! Here's the equation you need to use:

MESS = ((A + B + C + D) / G) + ((E + H + I + J) / F)

You'll notice that there are several different components to your MESS. First, your score depends on the amount and complexity of your historical data (ABCD). There really is a balance between amount and complexity where analysis pays off. Complicated datasets tend to create analysis paralysis, while overly simple ones tend to yield few powerful insights (if any). Second, your ability to handle the data complexity with analytical specialists (G) can help you maximize the value of the data.

Your MESS also incorporates the extent to which your organization is oriented toward learning and testing (EHIJ). Impatience, lack of testing, and “take your best shot and get it over” are counter-productive, and lead to disappointing (and sometimes dangerous) results. In turn, these failures undermine the test-and-learn approach even further, as you spiral down into a void of hunches, revolving door opinions, and business stagnation. Careful testing and analysis has proven again and again to yield significant improvements in marketing ROI (easily more than 10 percent, in my experience).

Finally, your MESS must incorporate the extent to which an opportunity exists for better results (F). Coordinating your paid search campaign with your media mix probably will not yield dramatic improvements in your conversion levels or ROI if you're already employing reasonably sophisticated budgeting and bidding algorithms.

In fact, the use of budget and bidding scenarios that use predictive models (WITHOUT media information) can yield significant benefits to your bottom line. Adding media data into those algorithms, in my experience, will produce gains in the 5-20 percent range.

Now, the drum-roll please ...

If your MESS is:

0 – 9 = Why are you reading this article? A lot of time on your hands? Is your company hiring?
10 – 19 = You're ready. Take a deep breath, then take the plunge.
20 – 29 = Don't start counting your chickens before they're hatched. There are several obstacles that must be overcome, and lower hanging fruit. Come back and re-take the MESS questionnaire in several months.
30+ = You're in deep ... water. Start bailing instead of looking at the stars.

For those of you with a high MESS (30+ bucket): It's good that you're reading this article, if just to realize how really far behind you are. How are you doing surviving?

For those of you in the 20 – 29 bucket: If you aren't yet doing basic ad copy and landing page testing, as well as budget and bid forecasting, then start there. The incorporation of media mix data into your strategy represents a layer of sophistication that builds on a foundation of data, learning, and analysis. Trying to jump to the front of the pack without paying attention to the fundamental foundations of paid search management involves a level of sophistication, focus and determination that eclipses your current situation.

For those of you in the 10 – 19 bucket: If the groundwork is ready for incorporating media mix into your paid search effort, then start assembling the data and getting the project onto the radar of your statistical analysts. It may take several weeks or more to produce solid results that produce actionable decisions (such as “Decrease your bids for top volume, non-branded terms by 50 percent 3 days after the TV campaign starts”). But what you should see come out of that coordination is a golden result – higher ROI and more conversions, as your paid campaign strategically capitalizes on the media environment.

Finally, those of you in the 0-9 bucket: Congrats! You're setting the pace for your competitors. They are coming after you, and want to take your house and job away. A consistent focus on coordinating your paid search with other media efforts should continue to yield dividends. Look for further processes efficiencies, and testing or analysis that clears up any lingering gaps in your knowledge.

In summary, the incorporation of media mix information into your paid search marketing is not without preconditions. There must be a reasonably rich set of data available, and the resources (analysts) to carefully examine it. Additionally, your organization can not be impatient or expect major increases in their efficiency (above and beyond the basics).

Indeed, you need to recognize that as you continue to improve your search campaigns, those improvements are harder and harder to achieve over time. Incorporating media mix into your paid search campaigns is such an endeavor, albeit with significant returns that can move your company to the forefront of the marketplace.

Pat Stroh is VP of analysis & decision support at SEM agency Impaqt. He spearheads analytical initiatives and decision support activities for Impaqt's search marketing campaigns, with a special focus on ROI-optimization.

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