How the Right Data Technology Can Fuel Your Organic Sales Growth

We’re all on a quest for organic sales growth. We all want to find ways to increase our conversion rate, improve our customer lifetime value, expand into adjacent markets, and launch new products successfully.

We’re all on a quest for organic sales growth. We all want to find ways to increase our conversion rate, improve our customer lifetime value, expand into adjacent markets, and launch new products successfully.

The problem is there are more ideas out there than we have time or money to implement. Do we try to target a fresh audience on LinkedIn, or do we invest in developing a new events business? Do we revamp our content marketing strategy to improve our conversion rates, or do we get into user experience redesign to help retention? With so many good growth ideas — and simultaneously so much pressure to grow our businesses — it can get stressful.

The sort-of good news is that data can help us optimize our decision making, so we can get the most bang for our buck with our limited resources. But here’s the rub: For most publishers, data is all over the place. It’s housed in every system under the sun, from the cloud to Excel spreadsheets to the old CFO’s hard drive to who knows where else.

Data is hot right now, so you might be panicking about the scattered state of data within your own organization. You might even feel tempted to go out and license the latest technology ASAP — maybe a CDP, DMP, or CRM.

Not so fast! If you take nothing else away from this article, remember this: Don’t spend a dollar on technology until you have a plan.

Now, I’m not saying don’t buy technology. These customer data tools are essential for leveraging one of our greatest assets, namely, a lot of information about our readers and customers. I’m saying approach this investment strategically. After all, a large technology investment that flops can be a fireable offense.

Where Do I Start?

If you’re going to spend money on technology, it has to be coupled with a strategy for either getting new customers or keeping existing customers.

Data technology can empower organizations in their quest for new customers in a number of ways. You can use data tools to evaluate the ROI of various marketing and sales channels to get more customers per dollar of overall marketing/sales spend.

Data can help you understand which content and actions reduce the sales lead time. Knowing what worked with your old leads enables you to move new ones down the funnel more quickly, and it makes life easier for your sales and ecommerce teams. Not only that, data can help you identify the predictors of a quality lead versus a waste-of-time lead (what we like to call a whale versus barnacle) so that you’re only sending marketing-qualified leads to your sales team in the first place.

Understanding various segments of your audience — otherwise known as personas or target audiences — can help you identify the groups that really jibe with your value proposition, so you can find the easiest markets to target. Plus, tracking how these segments react to various pricing, discounting, and bundling offers throughout their journey allows you to offer the right product to the right prospect at the right time.

When it comes to keeping customers, data technology can help you understand behaviors that lead to renewal or upsell versus behaviors that lead to churn. Understanding these actions and behaviors can also clue you into the things that customers love (and what they don’t like so much), so you can provide a better customer experience that leads to greater upselling and more repeat sales. Plus, you can create new products and services that suit your best customers’ needs to drive new revenue streams and encourage even greater retention rates.

How Do I Choose the Right Tech?

Selecting the right technology for your business starts with setting specific and measurable goals – and it’s a good idea to put them in writing. Once you do that, you can start looking at technology solutions that will help you achieve those goals.

If you implement a CDP, for example, what are you expecting to see? Maybe it’s a 20% increase in traffic, 30% increase in new business, and 15% increase in retention rates. Do the math to calculate the economic benefit of these results, and compare that to the cost of investing in the data technology. If you’re not happy with the ROI, either keep brainstorming to find new ways to drive revenue, or wait until you see a clearer path to ROI before making the investment.

How Do I Screen Vendors?

Just as important as the technology itself is the company and team behind it. When you’re considering your options, you don’t want a free dinner. You don’t want a fancy PowerPoint. You don’t want a flashy demo.

You want to be able to hand your strategy off to the vendor and have them show you exactly how their solution will deliver your desired results. How have they achieved similar results with other customers? What exactly do you need (or not need) in order to hit these goals?

If the vendor’s sales team doesn’t have the acumen to answer these questions, buyer beware. It may be a sign that the technology is a shiny new object, not something that will deliver ROI for your organization.

What Else Do I Need to Consider?

Don’t expect data technology implementation to be an overnight success. Think of it as a project to take on over a 12-month time horizon. The first step is a small one, and that’s listening to the right data. From there, you can analyze the data you’ve been listening to, and then, finally, take action on those insights.

It’s also important to remember that technology does not use itself. You need to properly staff and educate your team to act on the insights generated by the data tool you choose.

Implementing your new system will require a lot from the people in your organization. They need to learn how to use the new platform, spend time inputting data, assess and analyze the results of the information they’re receiving, make recommendations to leadership on how to change the business’s approach based on analytics received from the technology, and then make those changes happen.

Data technology can do incredible things to fuel your organization’s organic growth. But an investment in new technology is just that: an investment. You wouldn’t buy a house or put money in the stock market without doing some research and laying a solid groundwork first. The same must be true for your preparations to incorporate a new technology tool into your organization. When you properly strategize for, select, and resource your investment, you’ll be well on your way to predictable organic growth.

Why You Are Missing Out Without Conversion Tracking

Which digital marketing channels are driving the most leads and sales for your business? Are any channels just wasting your budget? Without properly set up conversion tracking, there’s no way to answer those two critical questions.

How can you tell if your new Google Ads campaign is improving your conversion rate? What percentage of visitors coming to your landing pages are there because of your Facebook Ads? You can’t get an accurate assessment of the ROI generated by your advertising efforts without implementing mechanisms to track visitor responses.

What Is Conversion Tracking?

Conversion tracking involves placing a piece of code on your website to track visitors and their actions. The data helps you understand their responses to various techniques used in your ad campaigns and different webpage designs. You can use conversion tracking for testing of keywords, redesigned landing pages, and new ad text.

Items You Should Be Tracking

  • Forms on your website (ex. quote requests, scheduled appointments, demo requests)
  • E-commerce sales
  • Coupon codes you give out as a way of encouraging people to visit physical locations
  • Phone calls

Here is what you gain by effectively tracking your digital marketing efforts.

1. Better ROI Tracking

You can add tracking codes to “Thank You” pages to monitor completed transactions by visitors and origination channels. That can tell you how many of those conversions came from visitors who clicked on specific advertisements. You can include tracking of signups, lead generation, or other items relevant to improving ROI.

2. Insights Into Campaign Successes

Some ads will perform better than others. Conversion tracking tells you how well specific keywords perform in attracting your target audience. You can also learn which ad campaigns to eliminate if they tend to draw visitors who quickly move away from your landing pages. Use information gained from your split testing efforts to tweak your keyword lists, ad copy, and landing pages for better performance.

3. Figuring Out What Content to Reuse

You want to stick with what works. Conversion tracking lets you know which content on your website attracted the most interest, or which campaigns helped drive higher-quality visitors. You want content that keeps visitors on your site who will eventually convert into a lead or sale.

4. Improved Audience Categorization

Segmenting audiences allows you to provide relevant content to those who visit your site or sign up to receive your email communications. Conversion tracking helps you figure out whether you have your contacts properly sorted for the type of information they receive.

Better categorization means your audiences aren’t sending your emails directly to the trash bin, or worse, clicking the “report spam” and/or “Unsubscribe” link. You also increase your chances of attracting the type of attention that leads to more conversions and better ROI.

5. Knowledge of Where to Direct Marketing Budget

Marketers running campaigns on a limited budget must maximize each dollar spent, while being cost-efficient. That allows you to create more effective campaigns that get the most for your money. You avoid dumping money into failing ad strategies and can direct those funds to higher-performing efforts.

Why Conversion Tracking?

Conversion tracking allows you to track and improve the ROI of your digital marketing campaigns by helping you identify your best-performing campaigns and eliminate those not delivering the desired conversion rates. It also helps you understand where you should be directing your budget across all the various marketing channels so you maximize every dollar invested.

Want more help tracking your marketing campaigns?  Click here to grab a copy of our “Ultimate Google Analytics Checklist.”

Understanding Your Google Ads Metrics With the Latest Interface

How do you know what the metrics in Google Ads mean and which ones matter the most? The latest version of Google Ads’ interface has a particularly large number of metrics, so it’s easy to get overwhelmed when you first log on.

How do you know what the metrics in Google Ads mean and which ones matter the most? The latest version of Google Ads’ interface has a particularly large number of metrics, so it’s easy to get overwhelmed when you first log on.

Each page has a table full of data, including a graph of metrics and various reports. It’s a little like looking at an airplane cockpit for the first time, with all its lights, switches and gauges. However, experienced advertisers know that all the information in Google Ads allows you to dig into your campaign performance and find ways to improve it.

Which Metrics Really Matter?

The most important Google Ads metrics include the following:

  • Cost-per-click (CPC)
  • Clickthrough rate (CTR)
  • Conversion rate
  • Cost-per-acquisition (CPA)

CPC

CPC is an advertising model in which an advertiser pays a website owner each time a user clicks on an ad. First-tier search engines like Google Ads typically use a CPC model, because advertisers can bid on key phrases that are relevant to their target market. In comparison, content sites typically charge per 1,000 impressions of the ad.

CTR

CTR, or clickthrough rate, is the ratio of users who click a link to the total number of users who view the ad. CTR generally indicates a marketing campaign’s effectiveness in attracting visitors to a website.

Conversion Rate

Conversion rate is the ratio of goal achievements to the number of visitors. It’s essentially the proportion of visitors who take a desired action as a result of your marketing activity. The specific action that a conversion rate monitors depends on the type of business you’re promoting. For example, online retailers often define a conversion as a sale, while services businesses consider other actions, such as a request for a quote, a demo sign up or a report download, when measuring conversion rate.

CPA

CPA, or cost per action, is the total cost of your ads divided by the number of conversions. Again, the specific action depends on the type of business you’re promoting. For example, CPA for online retailers is typically the cost per e-commerce sale. Services businesses typically measure CPA as a cost per lead. This number is critical, because it tells you if your campaigns are profitable or not.

How Can Metrics Help You Improve Performance?

Poor metrics can indicate courses of action that can help you improve your Google Ads campaign performance.

CPC

A high CPC could mean that you need to raise the quality scores for your ad, which could reduce the cost of each click. You can also accomplish this by using ad scheduling and geotargeting to ensure your website doesn’t show ads during times or in locations where you don’t do business. Additional strategies for reducing CPC include using demographic targeting, in-market audiences and remarketing to narrow your audience to just the people who are interested in your business.

CTR

A low CTR can indicate that you need to review the keywords and ad copy in your Google Ads account. For example, you should ensure that you’re only bidding on keywords that relate to your offers. You should also perform A/B testing on your ads to determine the factors that interest your prospects the most, whether it’s features, benefits or some emotional trigger. You can also improve CTR by ensuring that your ad takes up as much room as possible by implementing ad extensions.

Conversion Rate

A low conversion rate can indicate that you need to take a closer look at your landing pages, where visitors go when they click on an ad. These pages should be very clean and quick to load to ensure visitors don’t lose interest after they click. Your ads should always send visitors directly to a dedicated landing page, rather than just your home page or even a general landing page.

CPA

A high CPA means that you aren’t getting a good return on investment (ROI) from your ad spend. Possible causes of a high CPA include a high CPC or low conversion rate, which often means a poor choice of keywords and ad copy. Concentrate your budget on high-converting keywords with a high intent to buy.

Conclusion

Google Ads provides many metrics that can tell you how to improve website performance. However, this information can also be daunting to interpret if you don’t know what it means.  Follow the tips above to monitor your key metrics and make adjustments to improve your Google Ads performance.

Want more tips to improve your Google advertising? Get your free copy of our “Ultimate Google AdWords Checklist.”

 

1 Big Pitfall to Successful Demand Generation Digital Transformation

As marketing leaders, we sometimes inadvertently lead our teams astray. When we delegate the outcomes we want, and simultaneously drive a sense of urgency, our teams may skip important steps in their drive to achieve the outcomes.

As marketing leaders, we sometimes inadvertently lead our teams astray. When we delegate the outcomes we want, and simultaneously drive a sense of urgency, our teams may skip important steps in their drive to achieve the outcomes. Here is a classic example we see all too frequently with clients.

The Scenario

We start with the desired outcomes, of course. In demand generation, this is usually marketing-qualified leads (MQLs) or sales-qualified leads (SQLs), bookings and revenue. If this desired outcome was somehow unexpected, then a sense of urgency invariably accompanies it. So, in turn, we light a fire under our teams to quickly get some leads in the door, generate MQLs and SQLs ASAP.

The Result and the 1 Big Pitfall

We need to generate leads and MQLs? Let’s create a campaign! Yay! Design it this week, build it next week, QA and launch the end of the week, and leads will start pouring in subsequent to that. Oh, dear. If only it were that easy. Going straight from “we need MQLs” to “let’s create a campaign” means going from Step 1 to Step 8 and skipping six important steps.

  1. Generate new MQLs and SQLs
  2. Create a campaign!

Here are the six intervening steps you will want to ensure your team takes if you are to have successful demand generation campaigns and succeed in your digital transformation.

Preventing the Pitfall

Step 2. What Buying Stage Transition Are We Targeting?

Once we understand the outcome desired in Step 1, we must determine what customer buying journey stage we are targeting. Are we moving people from unaware to aware, or from aware to consideration, etc. If you haven’t defined the customer buying journey, stop and define at least one.

Step 3. What Persona Are We Targeting?

Don’t have any defined personas? Stop and define at least one. Having a clear picture of who you are targeting is a critical step to successfully achieving your outcome. Now that you have the persona selected, the team gets to review what channels the persona prefers, and the content preferences. Step 2 and Step 3 are interchangeable. I.e., there will be occasions where you perceive your funnel conversion rate from one stage to another is low, and you make the buying journey stage decision first. There will be other times where you recognize your funnel volume is low on a particular persona, and you make the persona decision first and the buying journey stage decision second. Regardless, you need to take both steps.

Step 4. What Problem Does Your Persona Have at This Stage?

The next question to answer, now that you have selected the target persona, and the current buying journey stage, is what problem do the members of it have at this stage that can be solved with your content?

For example, if you are targeting the Aware stage, and want to move them to Consideration, what information or education will trigger the buyers to sit up, realize they have been ignoring a pain in their sides that is curable, or that they have an opportunity to do something they have not done before, and they need to finally take action? The ideal content you send is most likely NOT product-centric. It will be customer-centric and it will have the buyer‘s challenge or the opportunity as the primary theme. It will be very narrowly focused around that theme.

We are looking for the trigger that will move this persona one step forward in the buying journey. We are not trying to move them all of the way to “closed won” with a single piece of content, or a single campaign.

Step 5. What Message or Content Addresses That Challenge or Opportunity?

Okay, we have the target persona, the buying journey stage they are in, the trigger we feel will tip them forward into the next stage in the buying journey. So now the question is, what content do we have that directly addresses this issue? Ignore the medium it is in for now, as repackaging it may not be hard. Focus on which Subject Matter Experts (SMEs) can or have already produced in terms of educational pieces of content that will be most effective in engaging the targets and moving them forward.

Step 6. What Is the Appropriate Medium for the Information?

All too often, we have clients ask us: “What is the hottest medium to use these days — video, white papers, webinars, slide shares, infographics, what?”

This is totally the wrong question! The answer depends on the message itself, and the persona and, to some extent, the buying stage they are in.

For example, if your target persona is a technical influencer, and uses a smartphone frequently to read email on the commuter train in the morning, sending a white paper would be silly, but a 2-minute video could work great … depending on the message you are trying to send. And the medium may also depend on the channels we pick in Step 7. Because more and more campaigns are becoming multichannel, it is likely you will end up choosing multiple media for the message, to match the multiple channels you use to engage the targets.

Step 7. What Combination of Channels Will We Use to Communicate That Content?

Next, we have to determine which channels will work for this persona. It is a good idea to use more than one channel to convey the same message to the same individuals. The results will simply be better, and the level of effort is not significantly more.

Some firms erroneously believe that paid media ads are only for top-of-funnel, new-lead acquisition. This is not true.

For instance, you can upload a list of email addresses into Facebook, or LinkedIn, match them against their data to create your new target list, and then do nurturing campaigns through those channels very economically only to your existing leads.

Step 8: Put It All Together

Now you are finally ready for Step 8. Let’s design a campaign based on all of the decisions made in Steps 2-7.  Now the cynics among you will say, “Hey, steps 2-7 are really part of basic campaign design, how can people be skipping them?”

The Pitfall You Just Avoided

Well, many firms don’t have defined personas and buying journey maps and here is what happens:

Step 1. CMO: We need more MQLs, urgently

Step 8. Team: Let’s design a campaign

  • An Email campaign, right? Blast everyone who is not a customer in our database, right?
  • 4 touches, check
  • 2 weeks apart, check
  • What offers can we put in there, a case study, an infographic, a research report and the last email is the call to action — “request a demo.” Check
  • Great, code up that campaign, we can get this out in under two weeks. Yay.
  • Count all the MQLs.

Conclusion

So, the message is this. If you urgently discover you need more MQLs, update your resume, not your campaign calendar. If you want to be successful in digital transformation, become more customer-centric, and approach customer engagement from the buyer perspective:

Think about what information they need first. Secondly, determine what content contains that information and then lastly, what channels and campaigns can convey that information to the recipients. And understand that one campaign does not produce a meaningful flow of MQLs or SQLs. Nurturing is a process, it requires commitment and it must be sustained over a longer period of time

Lead Generation Metrics — The Basics and Beyond

Lead generation metrics should help you understand not only what parts of your digital marketing are working, but what parts are generating the highest quality leads.

There are basic lead generation metrics that you must to be tracking in order to evaluate the success of your lead gen efforts. You’ll likely have to go beyond the basics to mine truly valuable insights about your efforts.

Here’s a list, that’s by no means comprehensive, of my favorite basic and more advanced metrics.

First, the basics.

Impressions

How many people are seeing your ad, your content or whatever it is you’re using to attract that audience? This is, to use another term, your reach. Your tracking and evaluation here should be on a per-channel basis, with an eye toward finding the channels that you are able to grow most cost-effectively.

Clickthrough Rate

CTR is the number of people who interact with your content. Typically, that means they click the ad or the link in your social media post, etc. (You might also want to track other types of engagement, like subscriptions.) The critical element of this metric is breaking it down to individual ads or content, including individual issues of your newsletter campaign. You want to know what is resonating with your audience and what is driving them to take action.

Conversions

A conversion can be many different things, depending on the goal you have for your lead generation campaign. (e.g. marketing-qualified leads, sales-qualified leads, etc.) Whatever action you deem to be a conversion, it’s generally a “state change” along the buyer’s journey. That can be a move from a member of the target audience who’s never heard of you to a website visitor to a prospect to a MQL to an SQL and finally to becoming a client. Each of those state changes is a conversion that should be tracked separately.

Conversion Rate

This calculated metric is a function of conversions divided by impressions. It’s worth tracking on its own, of course, but should also be evaluated with some latitude. That is, as you expand your reach and your impressions rise, you may have a less tightly targeted audience. Of course, you’d like your conversion rate to always rise. But if it falls while the total number of conversions rise, that’s not necessarily a bad trade-off.

With these data points solidly represented in our dashboard, we can move on to additional (and increasingly useful) measurements.

Cost per Lead

What does it take to move a prospect through a stage in the funnel? How does the cost compare with other methods? (Direct mail, trade shows, etc.) How do costs compare across the various digital channels you’re using? These are the metrics that will guide your spend going forward.

Leads per Channel

Another calculated metric worth adding to your dashboard. Here, you compare how many leads a channel is generating against all other channels. It’s an analog to conversion rate in that a channel with more leads generated from a smaller audience (impressions) might be a channel worth exploring more deeply.

Time to Conversion

This metric typically takes some aggregating of data across platforms, as you’ll want to note when each state change occurs. It’s valuable to know how long it takes a typical prospect to proceed through each stage. It’s even more valuable to know this on a per-channel basis. And more valuable still to know average time-per-conversion for those prospects that become clients. You can then tailor your programs to pay more attention to those prospects who appear to be on that “golden path.”

Customer Lifetime Value (CLV)

CLV should be calculated across the board and broken down by channel. A channel with a slightly higher cost per lead but a 10-time increase in CLV is a great channel!

Conclusion

You may find the able list of metrics daunting to consider, especially if you’re not gathering and reviewing any of them now. If so, there’s no reason not to start small. As you become more comfortable with the data, you can expand your dashboard to include a broader range of data points and a broader possibility of action points.

Marketing Success Metrics: Response or Dollars?

It’s tempting to ask about whether marketing success metrics should be response rates or money. But you don’t need to ask marketers what they want. Basically, they want everything.

It’s tempting to ask about whether marketing success metrics should be response rates or money. But you don’t need to ask marketers what they want. Basically, they want everything.

They want big spenders who also visit frequently, purchasing flagship products repeatedly. For a long time (some say “lifetime”). Without any complaint. Paying full price, without redeeming too many discount offers. And while at it, minimal product returns, too.

Unfortunately, such customers are as rare as a knight in white armor. Because, just to start off, responsiveness to promotions is often inversely related to purchase value. In other words, for many retailers, big spenders do not shop often, and frequent shoppers are often small item buyers, or worse, bargain-seekers. They may just stop coming if you cut off fat discount deals. Such dichotomy is quite common for many types of retailers.

That is why a seasoned consultants and analysts ask what brand leaders “really” want the most in marketing success metrics. If you have a choice, what is more important to you? Expanding the customer base or increasing the customer value? Of course, both are very important goals — and marketing success metrics. But what is the first priority for “you,” for now?

Asking that question upfront is a good defensive tactic for the consultant, because marketers tend to complain about the response rate when the value target is met, and complain about the revenue size when goals for click and response rates are achieved. Like I said earlier, they want “everything, all the time.”

So, what does a conscientious analyst do in a situation like this? Simple. Set up multiple targets and follow multiple marketing success metrics. Never hedge your bet on just one thing. In fact, marketers must follow this tactic as well, because even CMOs must answer to CEOs eventually. If we “know” that such key marketing success metrics are often inversely correlated, why not cover all bases?

Case in point: I’ve seen many not-so-great campaign results where marketers and analysts just targeted the “best of the best” segment — i.e., the white rhinoceros that I described in the beginning — in modeled or rule-based targeting. If you do that, the value may be realized, but the response rate will go down, leading to disappointing overall revenue volume. So what if the average customer value went up by 20%, when only a small group of people responded to the promotion?

A while back, I was involved in a case where “a” targeting model for a luxury car accessory retailer tanked badly. Actually, I shouldn’t even say that the model didn’t work, because it performed exactly the way the user intended. Basically, the reason why the campaign based on that model didn’t work was the account manager at the time followed the client’s instructions too literally.

The luxury car accessory retailer carried various lines of products — from a luxury car cover costing over $1,000 to small accessories priced under $200. The client ordered the account manager to go after the high-value target, saying things like “who cares about those small-timers?” The resultant model worked exactly that way, achieving great dollar-per-transaction value, but failing at generating meaningful responses. During the back-end analysis, we’ve found that the marketer indeed had very different segments within the customer base, and going only after the big spenders should not have been the strategy at all. The brand needed a few more targets and models to generate meaningful results on all fronts.

When you go after any type “look-alikes,” do not just go after the ideal targets in your head. Always look at the customer profile reports to see if you have dual, or multiple universes in your base. A dead giveaway? Look at the disparity among the customer values. If your flagship product is much more expensive than an “average” transaction or customer value in your own database, well, that means most of your customers are NOT going for the most expensive option.

If you just target the biggest spenders, you will be ignoring the majority of small buyers whose profile may be vastly different from the whales. Worse yet, if you target the “average” of those two dichotomous targets, then you will be shooting at phantom targets. Unfortunately, in the world of data and analytics, there is no such thing as an “average customer,” and going after phantom targets is not much different from shooting blanks.

On the reporting front — when chasing after often elusive targets — one must be careful not to get locked into a few popular measurements in the organization. Again, I recommend looking at the results in every possible way to construct the story of “what really happened.”

For instance:

  • Response Rate/Conversion Rate: Total conversions over total contacted. Much like open and click-through rate, but I’d keep the original denominator — not just those who opened and clicked — to provide a reality check for everyone. Often, the “real” response rate (or conversion rate) would be far below 1% when divided by the total mail volume (or contact volume). Nonetheless, very basic and important metrics. Always try to go there, and do not stop at opens and clicks.
  • Average Transaction Value: If someone converted, what is the value of the transaction? If you collect these figures over time on an individual level, you will also obtain Average Value per Customer, which in turn is the backbone of the Lifetime Value calculation. You will also be able to see the effect of subsequent purchases down the line, in this competitive world where most responders are one-time buyers (refer to “Wrestling the One-Time Buyer Syndrome”).
  • Revenue Per 1,000 Contacts: Revenue divided by total contacts multiplied by 1,000. This is my favorite, as this figure captures both responsiveness and the transaction value at the same time. From here, one can calculate net margin of campaign on an individual level, if the acquisition or promotion cost is available at that level (though in real life, I would settle for campaig- level ROI any time).

These are just three basic figures covering responsiveness and value, and marketers may gain important intelligence if they look at these figures by, but not limited to, the following elements:

  • Channel/Media
  • Campaign
  • Source of the contact list
  • Segment/Selection Rule/Model Score Group (i.e., How is the target selected)
  • Offer and Creative (hopefully someone categorized an endless series of these)
  • Wave (if there are multiple waves or drops within a campaign)
  • Other campaign details such as seasonality, day of the week, daypart, etc.

In the ultimate quest to find “what really works,” it is prudent to look at these metrics on multiple levels. For instance, you may find that these key metrics behave differently in different channels, and combinations of offers and other factors may trigger responsiveness and value in previously unforeseen manners.

No one would know all of the answers before tests, but after a few iterations, marketers will learn what the key segments within the target are, and how they should deal with them discriminately going forward. That is what we commonly refer to as a scientific approach, and the first step is to recognize that:

  • There may be multiple pockets of distinct buyers,
  • Not one type of metrics will tell us the whole story, and
  • We are not supposed to batch and blast to a one-dimensional target with a uniform message.

I am not at all saying that all of the popular metrics for digital marketing are irrelevant; but remember that open and clicks are just directional indicators toward conversion. And the value of the customers must be examined in multiple ways, even after the conversion. Because there are so many ways to define success — and failure — and each should be a lesson for future improvements on targeting and messaging.

It may be out of fashion to say this old term in this century, but that is what “closed-loop” marketing is all about, regardless of the popular promotion channels of the day.

The names of metrics may have changed over time, but the measurement of success has always been about engagement level and the money that it brings.

Don’t Do It Just Because You Can

Don’t do it just because you can. No kidding. … Any geek with moderate coding skills or any overzealous marketer with access to some data can do real damage to real human beings without any superpowers to speak of. Largely, we wouldn’t go so far as calling them permanent damages, but I must say that some marketing messages and practices are really annoying and invasive. Enough to classify them as “junk mail” or “spam.” Yeah, I said that, knowing full-well that those words are forbidden in the industry in which I built my career.

Don’t do it just because you can. No kidding. By the way, I could have gone with Ben Parker’s “With great power comes great responsibility” line, but I didn’t, as it has become an over-quoted cliché. Plus, I’m not much of a fan of “Spiderman.” Actually, I’m kidding this time. (Not the “Spiderman” part, as I’m more of a fan of “Thor.”) But the real reason is any geek with moderate coding skills or any overzealous marketer with access to some data can do real damage to real human beings without any superpowers to speak of. Largely, we wouldn’t go so far as calling them permanent damages, but I must say that some marketing messages and practices are really annoying and invasive. Enough to classify them as “junk mail” or “spam.” Yeah, I said that, knowing full-well that those words are forbidden in the industry in which I built my career.

All jokes aside, I received a call from my mother a few years ago asking me if this “urgent” letter that says her car warranty will expire if she does not act “right now” (along with a few exclamation marks) is something to which she must respond immediately. Many of us by now are impervious to such fake urgencies or outrageous claims (like “You’ve just won $10,000,000!!!”). But I then realized that there still are plenty of folks who would spend their hard-earned dollars based on such misleading messages. What really made me mad, other than the fact that my own mother was involved in that case, was that someone must have actually targeted her based on her age, ethnicity, housing value and, of course, the make and model of her automobile. I’ve been doing this job for too long to be unaware of potential data variables and techniques that must have played a part so that my mother to receive a series of such letters. Basically, some jerk must have created a segment that could be named as “old and gullible.” Without a doubt, this is a classic example of what should not be done just because one can.

One might dismiss it as an isolated case of a questionable practice done by questionable individuals with questionable moral integrity, but can we honestly say that? I, who knows the ins and outs of direct marketing practices quite well, fell into traps more than a few times, where supposedly a one-time order mysteriously turns into a continuity program without my consent, followed by an extremely cumbersome canceling process. Further, when I receive calls or emails from shady merchants with dubious offers, I can very well assume my information changed hands in very suspicious ways, if not through outright illegal routes.

Even without the criminal elements, as data become more ubiquitous and targeting techniques become more precise, an accumulation of seemingly inoffensive actions by innocuous data geeks can cause a big ripple in the offline (i.e., “real”) world. I am sure many of my fellow marketers remember the news about this reputable retail chain a few years ago; that they accurately predicted pregnancy in households based on their product purchase patterns and sent customized marketing messages featuring pregnancy-related products accordingly. Subsequently it became a big controversy, as such a targeted message was the way one particular head of household found out his teenage daughter was indeed pregnant. An unintended consequence? You bet.

I actually saw the presentation of the instigating statisticians in a predictive analytics conference before the whole incident hit the wire. At the time, the presenters were unaware of the consequences of their actions, so they proudly shared employed methodologies with the audience. But when I heard about what they were actually trying to predict, I immediately turned my head to look at the lead statistician in my then-analytical team sitting next to me, and saw that she had a concerned look that I must have had on my face, as well. And our concern was definitely not about the techniques, as we knew how to do the same when provided with similar sets of data. It was about the human consequences that such a prediction could bring, not just to the eventual targets, but also to the predictors and their fellow analysts in the industry who would all be lumped together as evil scientists by the outsiders. In predictive analytics, there is a price for being wrong; and at times, there is a price to pay for being right, too. Like I said, we shouldn’t do things just because we can.

Analysts do not have superpowers individually, but when technology and ample amounts of data are conjoined, the results can be quite influential and powerful, much like the way bombs can be built with common materials available at any hardware store. Ironically, I have been evangelizing that the data and technology should be wielded together to make big and dumb data smaller and smarter all this time. But providing answers to decision-makers in ready-to-be used formats, hence “humanizing” the data, may have its downside, too. Simply, “easy to use” can easily be “easy to abuse.” After all, humans are fallible creatures with ample amounts of greed and ambition. Even without any obvious bad intentions, it is sometimes very difficult to contemplate all angles, especially about those sensitive and squeamish humans.

I talked about the social consequences of the data business last month (refer to “How to Be a Good Data Scientist“), and that is why I emphasized that anyone who is about to get into this data field must possess deep understandings of both technology and human nature. That little sensor in your stomach that tells you “Oh, I have a bad feeling about this” may not come to everyone naturally, but we all need to be equipped with those safeguards like angels on our shoulders.

Hindsight is always 20/20, but apparently, those smart analysts who did that pregnancy prediction only thought about the techniques and the bottom line, but did not consider all the human factors. And they should have. Or, if not them, their manager should have. Or their partners in the marketing department should have. Or their public relations people should have. Heck, “someone” in their organization should have, alright? Just like we do not casually approach a woman on the street who “seems” pregnant and say “You must be pregnant.” Only socially inept people would do that.

People consider certain matters extremely private, in case some data geeks didn’t realize that. If I might add, the same goes for ailments such as erectile dysfunction or constipation, or any other personal business related to body parts that are considered private. Unless you are a doctor in an examining room, don’t say things like “You look old, so you must have hard time having sex, right?” It is already bad enough that we can’t even watch golf tournaments on TV without those commercials that assume that golf fans need help in that department. (By the way, having “two” bathtubs “outside” the house at dusk don’t make any sense either, when the effect of the drug can last for hours for heaven’s sake. Maybe the man lost interest because the tubs were too damn heavy?)

While it may vary from culture to culture, we all have some understanding of social boundaries in casual settings. When you are talking to a complete stranger on a plane ride, for example, you know exactly how much information that you would feel comfortable sharing with that person. And when someone crosses the line, we call that person inappropriate, or “creepy.” Unfortunately, that creepy line is set differently for each person who we encounter (I am sure people like George Clooney or Scarlett Johansson have a really high threshold for what might be considered creepy), but I think we can all agree that such a shady area can be loosely defined at the least. Therefore, when we deal with large amounts of data affecting a great many people, imagine a rather large common area of such creepiness/shadiness, and do not ever cross it. In other words, when in doubt, don’t go for it.

Now, as a lifelong database marketer, I am not advocating some over-the-top privacy zealots either, as most of them do not understand the nature of data work and can’t tell the difference between informed (and mutually beneficial) messages and Big Brother-like nosiness. This targeting business is never about looking up an individual’s record one at a time, but more about finding correlations between users and products and doing some good match-making in mass numbers. In other words, we don’t care what questionable sites anyone visits, and honest data players would not steal or abuse information with bad intent. I heard about waiters who steal credit card numbers from their customers with some swiping devices, but would you condemn the entire restaurant industry for that? Yes, there are thieves in any part of the society, but not all data players are hackers, just like not all waiters are thieves. Statistically speaking, much like flying being the safest from of travel, I can even argue that handing over your physical credit card to a stranger is even more dangerous than entering the credit card number on a website. It looks much worse when things go wrong, as incidents like that affect a great many all at once, just like when a plane crashes.

Years back, I used to frequent a Japanese Restaurant near my office. The owner, who doubled as the head sushi chef, was not a nosy type. So he waited for more than a year to ask me what I did for living. He had never heard anything about database marketing, direct marketing or CRM (no “Big Data” on the horizon at that time). So I had to find a simple way to explain what I do. As a sushi chef with some local reputation, I presumed that he would know personal preferences of many frequently visiting customers (or “high-value customers,” as marketers call them). He may know exactly who likes what kind of fish and types of cuts, who doesn’t like raw shellfish, who is allergic to what, who has less of a tolerance for wasabi or who would indulge in exotic fish roes. When I asked this question, his answer was a simple “yes.” Any diligent sushi chef would care for his or her customers that much. And I said, “Now imagine that you can provide such customized services to millions of people, with the help of computers and collected data.” He immediately understood the benefits of using data and analytics, and murmured “Ah so …”

Now let’s turn the table for a second here. From the customer’s point of view, yes, it is very convenient for me that my favorite sushi chef knows exactly how I like my sushi. Same goes for the local coffee barista who knows how you take your coffee every morning. Such knowledge is clearly mutually beneficial. But what if those business owners or service providers start asking about my personal finances or about my grown daughter in a “creepy” way? I wouldn’t care if they carried the best yellowtail in town or served the best cup of coffee in the world. I would cease all my interaction with them immediately. Sorry, they’ve just crossed that creepy line.

Years ago, I had more than a few chances to sit closely with Lester Wunderman, widely known as “The Father of Direct Marketing,” as the venture called I-Behavior in which I participated as one of the founders actually originated from an idea on a napkin from Lester and his friends. Having previously worked in an agency that still bears his name, and having only seen him behind a podium until I was introduced to him on one cool autumn afternoon in 1999, meeting him at a small round table and exchanging ideas with the master was like an unknown guitar enthusiast having a jam session with Eric Clapton. What was most amazing was that, at the beginning of the dot.com boom, he was completely unfazed about all those new ideas that were flying around at that time, and he was precisely pointing out why most of them would not succeed at all. I do not need to quote the early 21st century history to point out that his prediction was indeed accurate. When everyone was chasing the latest bit of technology for quick bucks, he was at least a decade ahead of all of those young bucks, already thinking about the human side of the equation. Now, I would not reveal his age out of respect, but let’s just say that almost all of the people in his age group would describe occupations of their offspring as “Oh, she just works on a computer all the time …” I can only wish that I will remain that sharp when I am his age.

One day, Wunderman very casually shared a draft of the “Consumer Bill of Rights for Online Engagement” with a small group of people who happened to be in his office. I was one of the lucky souls who heard about his idea firsthand, and I remember feeling that he was spot-on with every point, as usual. I read it again recently just as this Big Data hype is reaching its peak, just like the dot.com boom was moving with a force that could change the world back then. In many ways, such tidal waves do end up changing the world. But lest we forget, such shifts inevitably affect living, breathing human beings along the way. And for any movement guided by technology to sustain its velocity, people who are at the helm of the enabling technology must stay sensitive toward the needs of the rest of the human collective. In short, there is not much to gain by annoying and frustrating the masses.

Allow me to share Lester Wunderman’s “Consumer Bill of Rights for Online Engagement” verbatim, as it appeared in the second edition of his book “Being Direct”:

  1. Tell me clearly who you are and why you are contacting me.
  2. Tell me clearly what you are—or are not—going to do with the information I give.
  3. Don’t pretend that you know me personally. You don’t know me; you know some things about me.
  4. Don’t assume that we have a relationship.
  5. Don’t assume that I want to have a relationship with you.
  6. Make it easy for me to say “yes” and “no.”
  7. When I say “no,” accept that I mean not this, not now.
  8. Help me budget not only my money, but also my TIME.
  9. My time is valuable, don’t waste it.
  10. Make my shopping experience easier.
  11. Don’t communicate with me just because you can.
  12. If you do all of that, maybe we will then have the basis for a relationship!

So, after more than 15 years of the so-called digital revolution, how many of these are we violating almost routinely? Based on the look of my inboxes and sites that I visit, quite a lot and all the time. As I mentioned in my earlier article “The Future of Online is Offline,” I really get offended when even seasoned marketers use terms like “online person.” I do not become an online person simply because I happen to stumble onto some stupid website and forget to uncheck some pre-checked boxes. I am not some casual object at which some email division of a company can shoot to meet their top-down sales projections.

Oh, and good luck with that kind of mindless mass emailing; your base will soon be saturated and you will learn that irrelevant messages are bad for the senders, too. Proof? How is it that the conversion rate of a typical campaign did not increase dramatically during the past 40 years or so? Forget about open or click-through rate, but pay attention to the good-old conversion rate. You know, the one that measures actual sales. Don’t we have superior databases and technologies now? Why is anyone still bragging about mailing “more” in this century? Have you heard about “targeted” or “personalized” messages? Aren’t there lots and lots of toolsets for that?

As the technology advances, it becomes that much easier and faster to offend people. If the majority of data handlers continue to abuse their power, stemming from the data in their custody, the communication channels will soon run dry. Or worse, if abusive practices continue, the whole channel could be shut down by some legislation, as we have witnessed in the downfall of the outbound telemarketing channel. Unfortunately, a few bad apples will make things a lot worse a lot faster, but I see that even reputable companies do things just because they can. All the time, repeatedly.

Furthermore, in this day and age of abundant data, not offending someone or not violating rules aren’t good enough. In fact, to paraphrase comedian Chris Rock, only losers brag about doing things that they are supposed to do in the first place. The direct marketing industry has long been bragging about the self-governing nature of its tightly knit (and often incestuous) network, but as tools get cheaper and sharper by the day, we all need to be even more careful wielding this data weaponry. Because someday soon, we as consumers will be seeing messages everywhere around us, maybe through our retina directly, not just in our inboxes. Personal touch? Yes, in the creepiest way, if done wrong.

Visionaries like Lester Wunderman were concerned about the abusive nature of online communication from the very beginning. We should all read his words again, and think twice about social and human consequences of our actions. Google from its inception encapsulated a similar idea by simply stating its organizational objective as “Don’t be evil.” That does not mean that it will stop pursuing profit or cease to collect data. I think it means that Google will always try to be mindful about the influences of its actions on real people, who may not be in positions to control the data, but instead are on the side of being the subject of data collection.

I am not saying all of this out of some romantic altruism; rather, I am emphasizing the human side of the data business to preserve the forward-momentum of the Big Data movement, while I do not even care for its name. Because I still believe, even from a consumer’s point of view, that a great amount of efficiency could be achieved by using data and technology properly. No one can deny that modern life in general is much more convenient thanks to them. We do not get lost on streets often, we can translate foreign languages on the fly, we can talk to people on the other side of the globe while looking at their faces. We are much better informed about products and services that we care about, we can look up and order anything we want while walking on the street. And heck, we get suggestions before we even think about what we need.

But we can think of many negative effects of data, as well. It goes without saying that the data handlers must protect the data from falling into the wrong hands, which may have criminal intentions. Absolutely. That is like banks having to protect their vaults. Going a few steps further, if marketers want to retain the privilege of having ample amounts of consumer information and use such knowledge for their benefit, do not ever cross that creepy line. If the Consumer’s Bill of Rights is too much for you to retain, just remember this one line: “Don’t be creepy.”

How Much Should You Spend on Google AdWords?

One of the most frequent questions I receive about Google AdWords is, “How much should I be spending on my AdWords campaign?” That’s a great question, and the short answer is, “It depends.”

Editor’s Note: Don’t miss Phil Frost’s upcoming webinar “Old School SEO Is Dead: What you can do to adapt to Google and the new world of search marketing,” live on February 25. Click here to register.

One of the most frequent questions I receive about Google AdWords is, “How much should I be spending on my AdWords campaign?” That’s a great question, and the short answer is, “It depends.” One of the great things about AdWords is that it is highly customizable, allowing you to make the decisions that best fit your business needs. The downside is that it is not easy to see at a glance how best to manage your AdWords budget.

Fortunately, we have developed a formula that allows you to plug in your numbers and calculate a realistic budget. It breaks down into two phases: Testing and ROI.

Phase 1: Testing

When you begin your Google AdWords campaign, you will need to test several ideas to see what works for you and what doesn’t. While some campaigns are profitable right out of the gate, many others are not. Consider your testing phase to be a form of market research, and plan to invest those dollars without the expectation of getting them back.

Before you begin, gather the following information:

  • Target Keywords Cost Per Click (CPC): Google AdWords follows a pay per click (PPC) model. No matter how many times your ad appears, you only pay when a prospect actually clicks on it. For each keyword, you will pay a different amount of money for that click. This is known as the CPC, or cost per click. For example, Google estimates that “coffee shop” costs $2.90 per click, while “mortgage broker” costs $13.76.

Make a list of the keywords that you want to test, and then use the Google AdWords Keyword Planner Tool to estimate the CPC for each of those keywords. Remember that this is just an estimate, so your actual cost may be higher or lower.

  • Time Frame: How long can you spend in the testing phase before you need to see your results? This is partly dependent on your industry and the keywords you choose. Some keywords have a higher search volume than others, making it easier to get results in a shorter time frame. Also consider your normal sales cycle. Do customers tend to purchase in one day, or does it take months for them to make up their minds? The lower your search volume and the longer your sales cycle, the longer it will take for you to obtain accurate data.
  • Sales Conversion Rates: As a general rule of thumb it’s safe to estimate that 1 in 100 people (1 percent) who view an AdWords ad will click on it, and 1 in 100 clicks (1 percent) will convert into a paying customer. These are estimates, and your ads might drive more or less traffic, but they work for planning purposes in the testing phase.

Now you are ready to put together your testing budget:

  • Per Keyword Cost to Test: If you can turn 1 in 100 clicks into a customer, then the estimated cost per sale is the cost per click (CPC) divided by 1 percent. For example, a keyword that costs $3 per click will cost you an estimated $300 for one sale. Go through the same process for each keyword you want to test, and add up the results to get your total budget.
  • Monthly Testing Budget: To generate a per-month Google AdWords budget, divide your total keyword costs to test by the number of months you want to allot to the testing phase. For example, if your total costs calculated earlier are $2,000, then you could budget $500 per month for 4 months. Or if you wanted to test faster, then $1,000 per month for 2 months.

Phase 2: ROI

Once your testing phase is complete, and you have generated a handful of sales from your ads, then it’s time to move into the ROI phase. The goal here is obviously to maximize return on investment from AdWords.

What should your budget be in the ROI phase? If your ads are profitable, then the answer is you should ditch your budget altogether! If every dollar you spend nets you more than a dollar in sales, it only makes sense to invest as many dollars as possible.

While many businesses focus on writing better ads, which improves the AdWords quality score and reduces the cost per click (CPC), that’s only half of the equation. The real magic comes from the EPC, or earnings per click.

To find your EPC, just multiply your customer value times your conversion rate. Your Customer Value is the average amount that one customer spends on your product or service minus your fulfillment costs. Your conversion rate is the percentage of clicks that become paying customers. So if the customer value is $100 and you have a 1 percent conversion rate, your EPC is $1.00.

Why Is EPC so important?

Well, it tells you exactly how much you can afford to pay per click for every single keyword in your account! If you pay more than your EPC, then you’ll be unprofitable. If you pay less, then you’re profitable. It’s as simple as that.

That means the key to AdWords success is to maximize your EPC by increasing both your customer value and your conversion rates.

Google AdWords is a highly customizable and extremely powerful advertising network, but it can be a bit overwhelming for newcomers. That’s why I put together an AdWords checklist to help you get your campaigns set up for success. Click here to get my Google AdWords checklist.

PPC Shockers and Secrets

Pay per click (PPC), particularly Google AdWords, is a marketing channel that can produce profitable results for your business, whether your goal is lead generation or sales. I have been managing PPC for businesses, as an in-house marketing leader as well as marketing consultant, for over a decade now. Though the years, I have noticed many secrets to success that I wanted to share—especially with business owners and marketers that haven’t tried PPC yet.

Pay per click (PPC), particularly Google AdWords, is a marketing channel that can produce profitable results for your business, whether your goal is lead generation or sales.

I have been managing PPC for businesses, as an in-house marketing leader as well as marketing consultant, for over a decade now.

Though the years, I have noticed many secrets to success that I wanted to share—especially with business owners and marketers that haven’t tried PPC yet.

First, I’d like to clear the air about a big shocker … or actually a fallacy … that you need a big budget to run an effective PPC campaign.

You don’t. If you happen to have a large budget, your ads will be shown more and you can spread out your ad groups and test different types. With a smaller budget, you do need to be more judicious with your efforts. But if you market smarter, not broader, your campaigns can still produce positive results.

I have run PPC campaigns with total monthly budgets of $1,000. I have run campaigns with total daily maximum budgets ranging from $25 to $50. These campaigns brought in both sales and leads, despite their limited spending. But they do require active management, strategic thinking, deep PPC knowledge and refinement/optimization.

The PPC Tri-Pod
What is going to determine the cost and return of your campaign are three simple things I call the “PPC Tri-pod”, as it supports your entire PPC efforts:

  1. Keywords
  2. Creative (or banner ad, if it’s running on the display network)
  3. Redirect URL

So in order for you to get the most bang for your buck with PPC, you should be aware of a few things regarding the PPC Tri-pod:

Keywords. The more popular the keyword, the more cost per click (CPC) it’s going to have. So it’s very important to do your keyword research before you start selecting your keywords as you’re setting up your campaign.

I like to use Keywordspy.com. The “lite” version is free, but you can also upgrade to the full version and see more results and have more capabilities for a monthly fee. Google used to have its Keyword External Tool, which has since morphed into Google AdWords Keyword Planner. You need a Gmail account to access this free tool.

Either of these tools will allow you to enter keywords or keyword phrases and then view popularity (actual search results), as well as what the average CPCs are. This is important for your keyword selection and bidding. You can also type in your “core” or focus keywords and get additional ad group/keyword ideas. To help refine your search terms, you can also choose broad match, broad match modifier, phrase match, exact match and negative match.

If you pick a word that is too vague or too under-searched, your ad will not see much (or any) action. Impressions will either not be served, or if they are served (in the case of a vague word), it may cost you a high CPC. In addition, a vague keyword may not be relevant enough to get you a good conversion rate. Because you pay by the click, your goal is to monetize that click by getting an instant conversion. And conversions, my friends, will be the role of the landing page. I’ll talk about that more in a moment.

Creative. This is your text ad (or banner ad, if you’re running in AdWords’ display network). For Google to rank your ad favorably, and more importantly, for you to get the best conversion results possible—there needs to be a relevancy and synergy between your keyword, text ad and landing page. Google will let you know if you’re not passing muster by your ad’s page position and quality score. Once you’ve carefully researched and selected your ad group keywords, you’ll want to make sure those keywords are consistent across the board with your ad and landing page. Your text ad has four visible lines with limited character count:

  1. Headline (25 Characters)
  2. Description Line 1 (35 Characters)
  3. Description Line 2 (35 Characters)
  4. Display URL (35 Characters)

Your keyword must appear in your text ad, as well as follow through and appear in the content of your landing page.

This will give you a good quality rank with Google, but also help qualify the prospect and carry the relevancy of the ad through to the landing page. Why is this important? It helps maintain consistency of the message and also set expectations with the end user. You don’t want to present one ad, and then have a completely different landing page come up.

Not only is that a “bait and switch,” but it’s costly. Because you’re paying for clicks, a great ad that is compelling and keyword rich, but not cohesive to your landing page, will not convert as well as one that is. And your campaign will actually lose conversions.

Redirect URL. This is your landing page. Different goals and different industries will have different formats. A lead generation campaign, which is just looking to collect email addresses to build an opt-in email list, will be a “squeeze page.” This is simply a landing page with a form asking for first name and email address in return for giving something away for free—albeit a bonus report, free newsletter subscription or similar. It got its name because it’s “squeezing” an email address from the prospect. Some retail campaigns will direct prospects directly to e-commerce sites or catalog pages (as opposed to a sales page). Direct response online marketers will drive their traffic to a targeted promotional landing page where it’s not typically a Web page where there’s other navigation or distractions that will take the prospect away from the main goal. It’s more streamlined and focused. The copy is not technical, it’s compelling and emotional, like promotional copy you would see in a sales letter. The anatomy of your redirect URL will vary on your goal and offer. It will take optimization and testing to see what’s working and what’s not. And that’s par for the course. If you’re testing, I suggest elements that scream and not whisper, such as long copy vs. short copy, or headlines and leads that are different themes. However, no matter what your goal, whether it’s going for the sale or the email address, you still need keyword consistency between all creative elements.

Tips And Tricks For Maximum ROI
Whether you have a big or small budget, there are a few things I’ve learned during the years that help the overall performance of a PPC campaign. Some of these are anecdotal, so if you’ve seen otherwise, I suggest testing to see if it makes a difference to your particular industry.

Ad and Landing Page. In general, I have noticed that shorter, to the point, landing pages produce better results. And the rationale is quite obvious. People searching the Web are looking for quick solutions to a problem. This means your creatives have to not only be keyword rich, but compelling and eye-caching. You have seconds to grab a Web surfer’s attention and get them to click. In the same sense, the landing page has to be equally relevant and persuasive, and typically shorter in copy. Keep in mind Google has many rules surrounding ad copy development. So write your text ads in accordance to its advertising policy.

Price Point. Again, in my personal experience, most Web surfers have a price threshold. And that’s items under about $79. When running a PPC campaign, think about price points that are more tolerable to “cold” prospects; that is, people who haven’t built a relationship with you or know anything about you. They have no brand loyalty. They don’t know you from Adam. So getting a sale at a lower price point is an easier sell than a product you have that costs hundreds of dollars. Luxury items or items with strong recognition and brand loyalty are the exception to that rule. As a direct response marketer, I urge you to price test and see for yourself.

Campaign Set-up. There are a few tactics I notice that help with ad exposure, clicks and saving money. When you’re setting up your campaign you can day-part, frequency cap and run ad extensions. Day parting allows you to select the hours of the day you’d like your campaign to run; ad extensions allow you to add components to your text ad to help visibility and call to action—such as location, site links, reviews and more; And frequency capping lets you set a threshold on how many times you’d like a given person to see your ad (based on impressions).

PPC Networks. It’s smart not to put all your eggs in one basket. In addition to Google AdWords, try running campaigns on other PPC networks, such as Bing/Yahoo, Adroll (retargeting through Facebook), Advertising.com/AdSonar.com, SiteScout.com (formerly Adbrite.com), and Kanoodle.com. Then see where you get the best cost per click, cost per conversion and overall results.

I’ve only touched the surface here. There are more tactics and features that can help a PPC campaign’s performance. So get yourself familiar with it, read up on the best practices, and don’t be afraid to put your toe in the water. As with any marketing tactic, some channels will work for your business, and some won’t. But you won’t know unless you test. Just remember the foundation of success hinges on the PPC Tri-Pod. The possibilities are endless.

How Many Leads Do You Need?

One key to successful B-to-B lead generation programs is to calculate exactly the right number of qualified leads to provide to sales—as part of your campaign planning. If you generate too many leads, you’ll be wasting precious marketing dollars. If you generate too few, your firm may be at risk of missing its revenue targets, with potentially disastrous financial implications. Moreover, you’ll annoy your sales team by not supporting them properly. So, let’s look at a neat way to figure out in advance how many leads your company needs, so you can invest accordingly.

One key to successful B-to-B lead generation programs is to calculate exactly the right number of qualified leads to provide to sales—as part of your campaign planning. If you generate too many leads, you’ll be wasting precious marketing dollars. If you generate too few, your firm may be at risk of missing its revenue targets, with potentially disastrous financial implications. Moreover, you’ll annoy your sales team by not supporting them properly. So, let’s look at a neat way to figure out in advance how many leads your company needs, so you can invest accordingly.

This easy method uses your sales people’s quotas to back your way into the number of leads required, based on sales productivity per lead. You will need four numbers:

  1. The average revenue quota per rep, in the period, whether it’s a year, or a quarter, or a month.
  2. The average revenue per order, or per closed deal.
  3. The percent of their quota that the sales people generate naturally, without the help of leads. This revenue typically flows from repeat sales, from deeper penetration within the accounts, or from referrals.
  4. The conversion rate from qualified lead to sales.

The first three numbers are likely to come from a discussion with sales management and your finance department. The last number you probably have on hand, from sales and marketing experience.

Here’s an example of how to do this calculation, based on a set of hypothetical numbers that might be common in large-enterprise selling environments. We are saying that each rep is on the hook to deliver $3 million in sales in the period. As a first calculation, subtract out the percentage of that revenue that the rep can produce without any leads supplied by marketing. In this example, it’s 40 percent self-generated, leaving 60 percent, or $1.8 million, that the rep needs help with from marketing.

We divide that remaining revenue by the average deal size, which is $60,000 in this example, to get the number of closed deals that each rep, on average, needs to complete to deliver on the revenue quota. In this example, it’s 30 deals.

Finally, we divide the number of deals required by the lead-to-sales conversion rate, which is 20 percent in this example. Voila. Now we know that each reps needs, on average, 150 qualified leads to make quota.

You can also take this to the next step and calculate the campaign inquiries required by dividing the 150 leads by your inquiry-to-lead conversion rate. With that, you can plan your campaigns to generate enough inquiries for your pipeline that will convert to a known number of qualified leads, and thereafter to the needed revenue.

So, with this simple math exercise, you can avoid waste and keep your sales reps as productive as they can be. Do you use another method that you can share?

A version of this article appeared in Biznology, the digital marketing blog.