Nuts & Bolts: Why Mobile is Important to Your Paid Search Strategy

Analytics Mobile Nuts & Bolts

In this installment of the “Nuts & Bolts” series, which digs into the nitty gritty of paid search, I want to share with you some valuable findings on the importance of mobile in your paid search strategy.

In a PPC Workshop I presented recently, I outlined five ways analytics makes paid search campaigns better. Further, I recapped the three-part series on mobile search that explained the driving forces behind the explosion of mobile search (and why it will continue to increase), what this means to marketers, and how this affects your paid search strategy.

Links for further reading and learning occur throughout the slides. And if you would like to share the workshop, we’ve posted to SlideShare for your convenience. Just click on the LinkedIn button or the file’s title to be immediately signed into the SlideShare site.

3 Ways to Influence Google Quality Score

Analytics Quality Score

shutterstock_189431450In the last FirstWord blog post, you learned the “5 Critical Components of Google Quality Score.” Now, you’ll learn how to influence those factors using three basic tactics.

But first, a refresher course:

What is Quality Score? It’s the algorithm Google uses to estimate how relevant the ads, keywords and landing pages in your digital marketing campaigns are to someone seeing them after a search. A higher Quality Score means Google’s systems consider your ads, keywords and landing pages relevant and useful to each searcher’s particular topic.

The higher your ad scores, the higher your ad ranks in every search auction. And the more likely clicks will become sales. That’s why it’s important to do everything you can to drive your Quality Score higher. Now, here are three ways to do just that:

  1. Improve Clickthrough Rate (CTR) – As the most important factor in Quality Score, CTR should receive the most attention. Four simple adjustments can improve CTR’s and drive up Quality Score:
    • Keyword Negatives – Continually add new negatives to eliminate unwanted queries.  Run your Search Query Reports weekly to identify opportunities and reach beyond eliminating bad clicks. Look to eliminate irrelevant high-impression terms that can drive down CTR.
    • Match Type Breakout— Breakout keywords by match types and separate match types by campaign or ad group.  This will further group not only like terms, but like match types and increase CTR on better performing Exact match groups. In addition, shy away from Broad match and focus on Broad Match Modifiers to improve CTR.
    • Sitelinks – Add Sitelinks to all campaigns and use ad group Sitelinks, when possible, to deliver more relevant Sitelinks. Traditional Sitelinks may increase CTR by 15%, and Enhanced Sitelinks may increase CTR by 20%.
    • Targeting – Eliminate poor performing targets for greater CTR by using all the targeting options available, including GEO targeting, ad scheduling and bid modifiers.
  2. Landing Pages – Because Google will crawl landing pages to determine how relevant they are to each keyword, picking the most relevant, most granular landing pages possible is imperative. When possible, regularly adjust content on landing pages and/or create specific paid-search landing pages that align with keyword to improve Quality Score.
  3. Build Quality History – Set up every campaign the right way every time and manage each and every campaign on regular basis. That’s the only way to build the account history Google seeks to reward with high Quality Scores. This is where discipline comes into play; if you can’t execute a campaign the right way, then maybe that campaign shouldn’t launch.

In addition to these three tactics, practice Search Engine Marketing (SEM) best practices. In short, create a logical campaign structure, craft tight ad groups with similar-themed keyword clusters, develop granular ad copy using keyword themes within copy and, most importantly, continually test and tweak, tweak, tweak.

5 Critical Components of Google Quality Score

Analytics Quality Score

Paid Search is not “Set It & Forget It” media. If you want optimal results from Paid Search, you must build fundamentally sound campaigns, monitor their progress at every opportunity and continually tweak, tweak, tweak. Discipline is the way to win. And the key to winning anything is maximizing your scoring power.

That’s the reason Google calls its relevancy metric “Quality Score.” It’s the algorithm Google uses to estimate how relevant your ads, keywords, and landing pages are to a person seeing your ads. A high Quality Score means Google’s systems consider your ads, keywords, and landing pages relevant and useful to users searching a particular topic. The higher your ad scores, the higher your ad ranks in every search auction. The higher your ad ranks, the more likely clicks will become sales.

In other words, a high score increases your likelihood of winning business through Paid Search campaigns. And if you want to raise your Quality Score, you first have to understand how Google determines this metric. Google is protective of its algorithms, so I can’t say exactly how it’s done. But I can reveal the five most important factors:

  1. Click Through Rate (CTR) – CTR is a user influenced attribute so Google gives it the most weight. Theory is: Large numbers of users clicking your ad must correlate to a positive experience. So high CTR drives Quality Score higher.
  2. Ad Relevancy – Both closely related relevant ad copy and having the actual keyword within ad copy improve Quality Score.
  3. Keyword Relevancy/Campaign Structure – Google’s system looks for keyword relevancy across ad groups. When keywords within an ad group are closely related, Quality Scores go up.
  4. Landing Page Relevancy – The more relevant the landing page, the better Quality Score.
  5. Account History – The length of time a keyword has been active in an account impacts Quality Score, but more important than length of time is how the keyword has performed over time.

Knowing these five critical components leads the way to five techniques you can apply to building and adjusting Paid Search campaigns that will drive higher Quality Scores. And that will be the topic of my next FirstWord post. Stay tuned.

3 Tips for Managing Attribution Modeling

Analytics Attribution Modeling

For months, our rallying cry has been “Drop your Last-Click Crutch!

Our argument is straightforward: How can marketers track the digital pathway buyers followed to reach them if the only clue is the buyers’ final step?

Sure, not long ago, we had little choice but to rely on the last click. The data connecting each touch point along a customer’s path to purchase wasn’t available or reliable. What’s more is the tools for analyzing this type of information were neither sophisticated nor affordable.

And yes, time was spending most of your marketing time and budget figuring out whether or not marketing was working just didn’t make a lot of sense. What did make sense was giving the last marketing tactic in a campaign that produced a sale 100% of the credit, because the data was fresh and unambiguous. We knew it was real — even though we also knew a mix of campaigns and as many as five touch points preceded that sale. In those days, we just couldn’t see those facts in front of us.

Well, today we can. Google’s recent research tells us as many as nine of every 10 marketers has access to some form of analytics tool, and the reasons for using those tools are more compelling than ever:

  • 90 percent of media interactions today are screen-based, a statistic that includes TVs, PCs, smartphones and tablets
  • 67 percent of buyers start shopping on one device and continue on another.

In other words, today’s digital commerce is complex. In turn, Smart marketing dictates that you invest your budget dollars where they will do the most good. And in my last post, we offered four ways you can approach this analysis – i.e., we’re pointing directions for stepping beyond the last click.

We understand that throwing down that last-click crutch and venturing into new analytical terrain can be intimidating, especially without a trusted means of support. So, here are a few pointers for approaching attribution modeling with new techniques:

  1. Know Before You Go. Earlier, we referred to the way today’s customers come to your company as a digital pathway. So, let’s stick to the analogy. If you want to discover a route to a new destination, you look at a map. In the case of attribution modeling, you should plug data into your analytics tool – just like you enter addresses into mapping software before hitting the road. Be sure full details – tactics, dates, dollars, etc. — about each digital campaign are entered into your modeling software.
  2. Walk First, Don’t Run. Explore alternative attribution models one at a time before trying combined or comprehensive analysis with any given technique. Before attempting an obstacle course, walking along the path and examining each challenge is a great way to prepare and minimize stumbling when the time comes to run the race.
  3. Carry Your “Last-Click Crutch.” Ok, we confess we were going for dramatic impact when we told you to “drop” your crutch. But that doesn’t mean we believe you should disregard it. Last-click analysis plays an important role in attribution modeling. Your picture of your customers’ journey would be incomplete without being able to see their final steps. So, you shouldn’t lean on that crutch, but you should carry the knowledge of how to use it along your way.

Expect some confusion at first but your competency will grow with time. And after a few trips, you’ll be finding efficient shortcuts and some more scenic routes than you’ve traveled before.

4 Alternatives to Last-Click Attribution Modeling

Analytics Attribution Modeling

My last post framed today’s marketing challenge as investing budget dollars where those funds will do the most good – and doing it quickly and precisely.

And then, I posed this provocative question: How can you meet that challenge without practicing sophisticated attribution modeling?

By sophisticated, of course, I mean dropping your Last-Click Crutch and using the powerful attribution analytics available to you to dig deeper. Here are four attribution modeling methods worth exploring for your digital campaigns:

1.  First Interaction. In this model, you’re placing all your focus on discovering what caused a prospect to become interested in your products or services in the first place. Did they click on a banner ad? Search on specific keywords? However they got there, this view can be just as limiting as Last Click, if you apply it in isolation. You still would have only one touchpoint on which to base your marketing decisions – it’s just moved to an earlier point in the process.

2.  Position-Based. Now we’re getting somewhere. With this model you’re accounting for all the different positions in the sales funnel and weighing them based on what you believe to be most important. For example, you may give 40 percent of the weight to First Interaction, 40 percent to Last Click, and 20 percent to what happens in the middle. The key is it’s showing every single touchpoint throughout the sales cycle. As you learn more about what motivates your customers to action, you can adjust weighting to better reflect how they interact with your brand. You can set up multiple customer models to give weight to different touchpoints, too. You also can perform a great deal of customization based on what’s important to the sale. For example, you can make adjustments for time on your site, page views (the more pages viewed, the more credit a particular channel gets), position rules that weight the value of a conversion based on each interaction, and more.

3.  Time-Delay. As the name implies, while you’re still looking at the entire sales funnel you give more weight to actions that occur closer to the conversion. So, for example, while some credit is given to an organic search that occurred 30 days ago, it is not nearly as much credit as the banner ad that was clicked two days ago, or the paid social media ad that was clicked today.

 4.  Linear. This model is incredibly powerful, but also requires the greatest degree of expertise. Rather than working from a starting point, you are customizing everything, with many more parameters available to you. Really, it’s the best of all the other models, combining elements of Positioned-Based and Time-Delay. For example, you can look at media in the past and the actual media type. If you feel paid search is more important than organic search, you can adjust the weighting that way. You can look at the path to get to a conversion and/or you can look at the different interactions.

All this capability at your fingertips can be confusing at first. Your best approach is start slowly with one of the less complicated models, and as your competency grows move into Linear attribution marketing. The process will take time. Be patient, and tweak, tweak, tweak as you learn.

3 Reasons to Drop Your “Last-Click” Crutch

Analytics Attribution Modeling

We’re all experienced marketers here, no?

So, no problem posing a couple of tough questions, right?

  1. Are you practicing attribution modeling for your digital campaigns?
  2. And if you are, are you still leaning on the Last-Click Crutch?

It’s OK to admit it, because it’s understandable. Not long ago, we had little choice but to rely on the last click. The data connecting each touch point along a customer’s path to purchase wasn’t available or reliable. Moreover, the tools for analyzing this type of information were neither sophisticated nor affordable.

Spending most of your marketing time and budget to determine whether or not marketing was working just didn’t add up. So, if the last marketing tactic in a campaign produced a sale, we gave it 100% of the credit – even though we all knew a mix of campaigns and as many as five touch points preceded that sale.

But leaning on the last click is no longer a crutch we can afford. Here are three reasons why:

  1. Every transaction today is faster — We live in an “instant oatmeal, microwave popcorn” world. During the past 20-30 years, consumer expectations for speed have become increasingly greater. Millennials in particular are unaccustomed to waiting for anything. They want instant gratification and demand nothing less. This expectation is fueled by the fact that they literally have the world in their pockets. According to Nielsen’s 2014 Digital Consumer Report, nearly two-thirds of Americans now own a smartphone. As a result, shopping can occur anywhere, anytime at the speed of a mobile browser.
  2. Every market is larger — Thanks to the internet, remaining a local-only business largely is a matter of choice. Today your customers can come from anywhere around the globe. The number of mobile phone subscriptions worldwide is approaching 7 billion, according to research by McKinsey & Company. To put that into perspective, that is roughly equivalent to the total world population in 2014. In addition, nearly 3 billion people have internet access.
  3. Every store is more than a store — Up until the last decade, the basis of a retail transaction in a store was simple: customers walk in, see an item they’d like to purchase, hand over payment and walk out with the item. Of course, if they didn’t see something they wanted, or it wasn’t available in their preferred size, color, configuration, etc., they would walk out empty-handed. Internet shopping began to change that model. It opened up a larger world of inventory. If the item wasn’t in the store, the customer could check online and, if successful, have the item delivered. Then came “order online, pick up at the store.” Bottom line of this trend is: If you aren’t willing to manage inventory this way, customers will pull out their smartphones and find sellers who are.

These three reasons add up to a clear conclusion: Customers have the information, and the customer experience will determine who gets the sale. Marketers can’t afford to burn time and money guessing how to reach these customers. That’s our challenge today as marketers. Smart marketing dictates that we invest budget dollars where those funds will do the most good. And we need to act quickly and precisely.

So, one last question: How can you meet that challenge without practicing sophisticated attribution modeling?