Customer Data: The Solution to Lead Generation

More leads, please.

In most companies, it's an ongoing process to generate interested buyers to your product and services.

We want qualified leads that move effortlessly throughout the sales cycle.

But the problem lies in our preparation. Some of us just don't have enough information about our prospects.

The CSO Insight study reported that “42 percent of sales reps feel that they don't have the right information before making a call.”

Use accurate customer data to prepare your team. Knowing key insights can make or break the deal.

Power up your data profile. Leverage it to produce more qualified leads.

Gathering Reliable Data

Based on an Ascend2 study, “35 percent of those surveyed said the biggest barrier to lead generation success is the lack of quality data.” Your data should tell a vivid story of your customer.

To gather reliable data, track anonymous users who visit your website. Watch leads interact with your content via session replays.

Ask for feedback from current customers. Monitor the trends of loyal consumers.

B2B marketers must also “embrace more third party and real-time data sets to really understand buyer's across the entire customer journey.” For example, that may include using social logins to access a prospect's profile information.

Data is widely available. Your team must decide which acquisition channels work for your company.

What's the best way to collect email addresses? Or how can you quickly accumulate customer preferences?

“Understanding who your customers are and, in turn, what they like, will undoubtedly enable you to increase conversions and sales. Make it easy for your customers to share their data with you, and use that data to keep them engaged with your business,” says Josh George, a senior applications engineer at Lyons Consulting Group.

Know who you're serving. Collect valid data for better results.

Enhancing Buyer Personas

Get inside your prospects' minds. Map out your ideal customer to understand their reasons for buying.

But, what's the point?

Buyer personas are roadmaps to navigating through your prospects' interests, dislikes, and habits. If you're aware of their behaviors, your team can create targeted solutions.

“By developing research-based buyer personas, you can create effective, highly targeted marketing campaigns. Each piece of communication ties back to your buyer personas so that every message addresses relevant pain points and positions your software as a viable solution,” states Brie Rangel, Account Strategist at IMPACT.

Knowing the basic demographics of your buyer is a given. Your team's goal is to dive deeper. Learn your customers' goals, challenges, and personal story.

Below is an example of a buyer persona for a specific startup founder. The story section offers a complete picture of the prospect, everything from the stage of his product to what he does for fun.

The role of customer data is to provide accurate information for your buyer personas. You don't want to waste time selling enterprise-level B2B SaaS software to a B2C startup.

Moreover, inaccurate buyer preferences and habits will leave both the prospect and sales rep frustrated. So, double-check your personas.

Because in the end, your mission is to match your product with a qualified lead. That's how you bring in sales.

“Use personas to spend more time with qualified leads, because they're the ones who are most likely to turn into those long-term customers you're looking for,” says Nicole Dieker, freelance writer and copywriter.

Enhance your buyer personas. Use data to add a face to the customer.

Segmenting Your Audience

After learning your customers distinct behaviors, it's time to serve those individual needs.

It makes no sense to group everyone together.

If Sally specifically likes apples, why send her emails about oranges and grapefruits? Instead, educate her about the difference between gala apples and pink lady apples.

That's a mental hurdle for most SaaS teams. We assume if our customers like X; they will definitely love Y. It isn't always that simple.

Segmentation comes in many shapes and sizes. From geographical to behavioral differences, your customers vary. And it's up to your team to discover how to connect with them.

You might consider a city in a particular state or the buyer's readiness to purchase. Work with your team to develop a goal.

Define your reason for segmentation. Experienced marketing and product leader Doug Goldstein offers the following common segmentation objectives:

• Create segmented ads & marketing communications


• Develop differentiated customer servicing & retention strategies


• Target prospects with the greatest profit potential


• Optimize your sales-channel mix

Segmentation is impossible without customer data. Add insights derived from analytics to guide how you group prospects.

And don't be afraid to experiment. Testing is how you'll discover the right messaging for your sales reps. Plus, it can help you market product information on your site.

“When practicing website optimization, leveraging customer segmentation provides a framework for running intentional, well-hypothesized experiments on your website that drive value,” writes Junan Pang, a solutions architect at Optimizely.

Segment your audience to deliver more personalized and timely experiences. With a segmented list, you'll be able to target the right services to interested buyers.

Building The Relationship

You can collect the data, create the buyer personas, and segment your audience. But all that data can't substitute customer relationships.

And that's where most businesses miss their opportunity.

“[C]ompanies often manage relationships haphazardly and unprofitably, committing blunders that undermine their connections with customers,” states Jill Avery, a senior lecturer at Harvard Business School.

Customer data is intended to facilitate the relationship between the sales rep and the buyer. However, research shows that companies without sophisticated data management tools “derive erroneous results that annoy customers, resulting in a 25 percent reduction in potential revenue gains.”

Don't attempt to foster a customer relationship with poor-quality data. If you do, prospects will seek out your competitors.

TechTarget executive editor Lauren Horwitz and SearchCRM site editor Tim Ehrens agree:

“Customer data management often falls to the bottom of the priority list. Organizations get bogged down with more pressing issues, such as cutting costs or keeping daily operations running. But relying on poor-quality customer data almost always frustrates customers - and many of them take their business elsewhere.”

Relationships are built on human-to-human contact. That means being genuinely interested in your buyer's concerns.

How can you make their lives better? Where can you offer convenience?

And sometimes your product won't be the solution. Yes, your SaaS service may not be the best option for that particular person.

Sales teams must recognize that it's okay to remove unqualified prospects from the pipeline. This action should be commended, not frowned upon.

Use customer data as a tool to score leads. Then, gain insight on how to target prospects that matter to your company.

Data shouldn't supplant the customer relationship. Make the human connection.

Go for the Data

Your team needs qualified leads. Focus on customer data as a solution.

Gather data from reliable sources. Use buyer personas to target your audience. Segment their behavior to create a personalized approach. And focus on building relationships throughout the sales cycle.

Want more leads? Go for the data.

About the Author: Shayla Price lives at the intersection of digital marketing, technology and social responsibility. Connect with her on Twitter @shaylaprice.

The Hidden Side Effects of Using Big Data to Better Understand Your Customers

When it comes to better understanding your customers, you likely leverage every possible resource from personas to mapping the customer experience journey.  For marketers, big data is a boon – it's a gold mine of information that, to be sure, requires a bit of digging through the dirt to get to the real treasure.

Big data has been used to tout everything from customer sentiment to fraud prediction. By letting computers do what they do best, it is believed that crunching all that information can lead to some pretty significant correlations – between click streams, geographic location, and even transactional data. Tying it all together helps bring the customer service lens into even greater focus.

With that being said, however, relying too much on big data has its drawbacks.  Beyond the fact that we're just starting to understand what's out there and how it's all relatable, big data should not be looked at as a marketing or customer service panacea.  In fact, there are a lot of areas where relying too much on big data to better understand your customers can have the opposite effect, like these:

Lack of Availability

Let's say you're shopping online for a new pair of shoes. You're scrolling through pair after pair on your cell phone until you find the perfect pair. Unfortunately, they're backordered.  You want to be notified when more are in stock, but you're not sure how to do that.  You tap for customer service. You're invited to type in your question and see a list of canned solutions.  That's a bit too cumbersome so you look for a way to contact a representative.

Instead, you're asked to submit your question to a helpdesk or online community. Trying to fill out a trouble ticket, you see that the service isn't compatible with mobile. You give up in frustration. Shortly thereafter, you get an email reminding you about the item you were interested in, and asking how the company can do better.

If you're visualizing a cartoonish response of steam coming out of your ears from anger and frustration, now you can imagine the limitations that big data has.  Perhaps the only retailer to truly get a handle on big data at this level is Amazon, and they've been able to integrate unimaginable reams of data seamlessly while being able to grow and scale their company with consistency.

Amazon had to grow and scale its operations – and quickly, yet they still deliver consistently high-rated customer service thanks to big data analytics.

When the service you need isn't available, you grit your teeth for long wait times ahead, and test your patience with the poor rep that has to look up the details of the backordered product in a sea of potential choices. The point is, Big Data shouldn't just be pored over by analytics experts, but made available to everyone at every tier in the organization.

Rush to Judgment and Unrealistic Expectations

Big data is the foundation of a perilously-positioned scale. On one end, you have the camp that's rigid and inflexible. Things have always been done a certain way, and the deluge of big data isn't going to change that. These companies risk getting outmaneuvered by their more proactive competitors. They make hasty decisions that may not always be backed by data science, and then backpedal when things go south.

At the opposite end, there are those who are positively drowning in analytics. They're so swallowed up by data that they hesitate to make any decision without consulting the numbers like some kind of oracle. They shrug off their “gut feelings” or intuition because the data doesn't account for that.

There's no doubt that big data is changing the way we market, but as many industry trends go, it can easily be blown out of proportion into something it's not. People are complex, self-serving, habitual, ever-changing creatures. Trying to make sense of that is not something that can be done overnight. It requires careful planning, an understanding of the different “pools” of information the data is drawing from, and one's own understanding of their target market to fully grasp.

Otherwise you end up with complex, complicated decisions that are impossible to predict and frustrating to implement.

Data Modeling Difficulties

In order to get the most out of big data, it has to be modeled in order to bring the value it's so often associated with to customer service, which in turn trickles down to the customer. At its core, Big Data is raw, unfiltered and largely noise. It's not structured, organized or clean.  The only system currently out there with the power to tackle such large scale information is Hadoop, which has been around since the early 2000s.

Hadoop is the closest thing available to enterprise-grade big data analytics. Image source

Currently there is no user friendly, on-demand and easily implementable enterprise data modeling system. There are many ways to tackle the big data noise, however, but many data models hit common obstacles including not being able to scale accordingly or organize the data in a sensible way, and still fewer work with existing analytics platforms and CRM information.

Just having the data is no longer enough. Making it accessible and understandable to everyone is the challenge today's modeling apps have to fix.

Pure Complexity

And finally, let's face it, we're only beginning to scratch the surface of what's out there. And yet it keeps growing and growing.  Costs go down, availability of information goes up.  Despite all its lucrative potential, big data can't replace people. When insights are gleaned from data scientists, they're passed on to managers and then employees.  If there's not a process in place to better understand and leverage the information you continue to gain, it's practically worthless.

The bottom line with using big data to better understand your customers is that there's a lot of expectations of what it can or cannot do. With such a wave looming overhead, it's easy to want to stand back and wait.  But just as the internet itself was once looked at as being “just a fad”, so too is big data poised to completely change what we know about our audience.

Being able to turn this information into insight is a challenge – but one worth tackling. We all know what happens when there's a rush to implement without a goal in mind.  Knowing the issues ahead of time can help you plan out a strategy that takes all of these points into consideration as you all work together toward a common goal – making sure every customer is exceedingly satisfied, again and again.

What are Your Thoughts on Using Big Data to Better Understand Customers?

Do you think big data is still in its infancy with regard to its use in customer analytics? Or do you think we simply lack the tools and understanding to make the most of it? What tools are you currently using to make sense of the data you collect? Share your thoughts and comments with us below.

About the Author: Sherice Jacob helps business owners improve website design and increase conversion rates through compelling copywriting, user-friendly design and smart analytics analysis. Learn more at iElectrify.com and download your free web copy tune-up and conversion checklist today!

What the 1960s Can Teach You About Growth Hacking

Growth hacking is an evolution.

Not a revolution.

It takes a different skill set. A new way of thinking.

However, at the end of the day, a lot of what you're doing still looks and sounds like real marketing.

Not today's misappropriated use of the word, but the good stuff originally developed back in 1960s.

Here's why.

Where Did Growth Hacking Come From?

Sean Ellis gets credit for initially coining the term that would eventually send startup peeps into a frenzy. (And for the first time in their lives, not completely abhor the concept of marketing or sales.)

Sean's concept came from initial failed attempts to hire data-driven, technical people focused on growing products or companies.

Instead, most of the 'marketing backgrounds' he saw made them great at communication, PR, and other classically defined marketing skills. Yet little focused on this new way of obsessing over conversions first.

These skill sets, while important, also aren't completely necessary in very early stage startup companies, as QuickSprout excellently points out in the Definitive Guide to Growth Hacking. They also carefully point out that both skill sets are still very important – one's just right for different circumstances.

But the problem comes when it's asserted that growth hackers are fundamentally different than marketers. Even the sage Fred Wilson got this wrong.

Are the two things so interlinked really all that different?

I'm not so sure.

Here's why, and where the confusion stems from.

The Great 'Growth Hacking' Hoax: Why Marketing Isn't Advertising

It's not growth hacking's fault.

For years, 'marketing' has been masquerading as 'advertising'. Inside most companies, the 'marketing department' does little more than work with advertising agencies or pick advertising channels.

Only in a rare case are they responsible for actual, you know, marketing.

Years ago, like way back in the 60s, the marketing mix was developed to provide a framework of all the roles and responsibilities that marketing influences.

And what you'll quickly notice, is that unlike today's bastardized version of marketing, this one actually includes a few other key areas like Product, Pricing, and… wait for it… Distribution (we'll come back to this last one in a minute).

Now is the marketing mix the end-all-be-all? Of course not. Sure, there's flaws.

But the central idea is strong and valid. And it can be perfectly highlighted with a simple story.

Walk into any car rental agency right now. Or retail. Or food. Movie theater. Take your pick.

What you'll encounter, is numerous dealings with the lowest paid, most underappreciated people in a company. And they'll treat you as such. Your experience with each person (who undoubtedly hates their job and questions their existence) colors your worldview of that brand forever.

What do you call that? Who's responsible for putting these ingrates in direct contact with customers on a daily basis? Customer service? Operations?

Now walk into an Apple store or a Four Seasons, and you'll undoubtedly #humblebrag to your friends on Instagram how helpful and awesome they were.

That's marketing. Even Fred Wilson readily admitted that customer service is one of the best forms of marketing for startups. And under the classic definition, it is.

The long-winded point here is that true marketing isn't advertising. Or PR. Or sales. It's all this junk that ultimately gets a customer to buy your stuff.

Or 'convert' and become a 'user'.

Peter Drucker, the OG, said the “aim of marketing was to make selling superfluous”. Obviously that's not defined or limited to a single person or department within an organization. And that's where the confusion stems from.

Growth hacking definitely has some unique characteristics that make their objective different than say, these other brand marketers who obsess over fuzzy intangibles all day.

But at the end of the day, a lot of what they do still looks like classic marketing.

Let's get specific.

If you try researching the difference between marketing and growth hacking, you'll see this article from The Next Web. A reputable, tech savvy site that's going finally lay the issue to rest. Perfect.

And it's a good read, which culminates in pointing out the laundry list of tactics that commonly differentiate growth hacking from marketing.

However, when you really start to analyze these tactics under a broader understanding of what marketing is or involves, you'll quickly start to see that these new-fangled tactics still look a whole lot like mid-century marketing.

When you get right down to it, a lot of the daily activities that define growth hacking resemble much of the same seemingly outdated marketing concepts from nearly 50+ years ago.

Again, let's get specific.

Let's take a look at some of the most fundamental 'growth hacks' used by successful startups over the past decade to reverse-engineer their meteoric rise.

Example #1. Product Hacks

Long before Gmail, there was Hotmail.

The idea of free email, at the time about twenty years ago, was kinda nuts. And it also presented a few obvious drawbacks to classic growth methods like advertising.

(Yes, even Stone Age Startups understood how CAC affects LTV. That wasn't just a YC thing for you millennial hipsters.)

Instead, Hotmail decided to leverage their existing 20,000 user base to kickstart one of the first examples of 'viral acquisition'.

In the bottom of each email, they added the simple tagline: “Get Your Free Email at Hotmail”.

Commonplace now, but keep in mind that this simple edit was pretty revolutionary at the time. Within six months, their userbase shot up to a million users.

Fast forward a bit, and another Silicon Valley darling was quickly finding out that paying more for a new customer than they're worth is a recipe for disaster (and bankruptcy).

In response, they created a simple referral program that resembled Hotmail's early tactic. Each new person that signed up for an account through this referral process got 500MB of free storage.

And in a little over a year, Dropbox grew from 100,000 users to 4 million.

Now there are many reasons these tactics succeeded. For one, getting something (for free) from your friend is a more compelling proposition than buying from a stranger over a questionable banner ad.

However, these are still simple product decisions too at the end of the day. (1) You have to have a good product to begin with – otherwise all the Promotion in the world won't help. And (2) creating new features in the product are what enable it to be shared through a referral mechanism.

But it also brings up an important concept from, you guessed it, the 60s.

In marketing promotion, there's Reach. And Frequency.

1. Reach: The number of new, unique people your message is seen by.


2. Frequency: The number of times that message reaches these people.

Admittedly, very simple. But also effective.

You'll notice that in both cases, Hotmail started with an initial 20,000 users while Dropbox had 100,000. If you're going for viral growth through recommendations, you need an existing user base to tap.

Why? Reach and frequency.

Wanna make numbers go up? Increase those two things.

The first is pretty easy. Just get more eyeballs to see your message.

Here's how.

Example #2. Distribution Hacks

Back in the day, distribution used to be more focused on Place.

That's because we lived in small towns and cities where you literally had a physical storefront. And even when times evolved, when products needed to be shipped across different factories or warehouses or retailers, you relied on heavily on distribution.

Technically, it means the “process of making a product or service available for use or consumption by a consumer or business user, using direct means, or using indirect means with intermediaries”.

That brought about different distribution methods like intensive, exclusive or selective (all of which mean exactly like they sound).

Today, this all seems archaic because you're mainly going direct to consumers through the interwebs.

But here's the important part, summed up by Wikipedia:

“The role of the marketing channels is not only focus on the participate in demand satisfaction by offering goods, but also need to stimulate demand through information, creating proximity and promotion by customer (Balasecu, 2014). In other words, distribution channels for the product is a system process.”

Distribution hacks are some of the most common in growth hacking lexicon, and it's roots are still firmly planted in the work from previous decades.

Airbnb didn't magically become the one-stop shop for letting strangers crash on your couch. No; they 'borrowed' (or ripped off) Craigslist's user base (thereby massively extending their own distribution). They created simple tools to allow Airbnb users to also get their properties in front of the massive number of people already searching and browsing Craigslist.

Image Source

This approach is nothing new.

Back in the good old days, YouTube used a similar form of 'platform hacking' (read: distribution) to piggyback on MySpace's success (and userbase of around 25 million uniques in 2005). Unlike many other video platforms at the time, YouTube openly allowed (and encouraged) users to take advantage of their embed code and spread their content to larger platforms like MySpace.

Facebook used selective (or exclusive) distribution when they started off as a closed network only open to specific colleges. That exclusivity idea was then borrowed by Pinterest who initially used invite-only status to increase their desirability and cachet.

In each case, distribution – a classic marketing consideration – was central to growth.

Example #3. Promotion Hacks

Despite the semantic issues already discussed at length, advertising still plays a role in today's 'growth hacking' playbook.

Look no further than Eric Ries' Lean Startup (which I can't believe was published in 2011 already), where advertising shows up as one of the three engines of growth to grow a sustainable business.

Paid acquisition, once again, isn't some completely brand new concept that evolved from the halls of MIT or Stanford. Instead, it's been employed successfully for half a century since the Mad Men era.

Sure, advertising channel options were incredibly limited back then. Which meant it was far easier to get your stuff to stick out. And sure, they didn't have fancy cohort analyses or funnel tracking tools, instead largely relying on correlation measurements to sales.

But still.

Make more money than you spend ain't an original equation. And it's especially useful in today's world, where let's face it: true virality like some of the earlier examples is incredibly rare (not to mention, borderline lucky).

Just look at Noah Kagan at AppSumo, who has spent over $2 million on ads to profitably grow their business.

Image Source

Or Netflix spending around $18 bucks for a subscriber when they make like $300 on each.

Or Groupon.

(Don't laugh. They still went public, bro.)

Sure they spent a sh*t-ton to do it, reportedly almost $200 mill in a single quarter according to the SEC. But that also helped them gain 33 million new subscribers. AND GO PUBLIC.

Point is: paid acquisition isn't a 'hack'. It's just called good (read: not terrible) advertising.

A few minutes ago you read about Reach, which can be increased through distribution and obviously advertising.

However advertising can also help bolster Frequency, which is important considering its curse (as Seth Godin describes it):

“The best members of your audience, the ones who are listening the most carefully, have to be bored/annoyed at the messages that show up after they take action. Some people pledge the first day of pledge week, or buy the book the day it comes out. Those folks don't want or need to hear the message again.”

“Worse, frequency creates a culture of less engagement. Since we know that just about every important issue, opportunity or warning is going to be repeated a few times, we don't engage as much. Why bother to listen, we say, they'll just repeat it.”

The world ain't as simple today as it used to be. A single ad or message won't get someone to convert.

But multi-channel marketing, complete with remarketing ads or utilizing custom audiences on Facebook, provide another new twist on an old stand-by marketing principle.

Conclusion

Growth hacking can involve mind numbingly complex techniques to obsessively grow a new product.

It's difficult to pull off and takes truly creative thinkers who're able to blend strategy with technical chops.

But at the end of the day, a lot of what they're doing still sounds a lot like marketing when you think about it.

Not today's watered-down version of advertising or PR. But true marketing, how it was envisioned over half a century ago, at its theoretical high point.

Those days weren't perfect. And the models espoused can seem a bit dated at times.

However, you might be surprised to find that your new brilliant growth hacking idea didn't come from hitting refresh on Hacker News, but instead from looking through a few dusty books from the 60s.

About the Author: Brad Smith is a founding partner at Codeless Interactive, a digital agency specializing in creating personalized customer experiences. Brad's blog also features more marketing thoughts, opinions and the occasional insight.

5 Actionable Google Analytics Reports to Improve Your Marketing Today

This isn't a 101-style post.

It's assuming you've got the basics down.

You've got a simple analytics framework down. You've got Goals or Events set-up (properly).

But you want action.

You want to figure out how to move the needle in as short amount of time as possible.

Counterintuitively, you shouldn't waste time with A/B testing. The good news, is that you also don't need to start creating a bunch of new content or pages either.

Instead, you should be looking for the current changes that will yield the highest return. Lurking deep inside Google Analytics, you can uncover tremendous opportunities by simply optimizing or fixing what you've already got.

Best of all, you're not guessing. You're coming up with new ideas, implementing them, watching the results and iterating.

It's informed. Predictable. And best of all, reliably successful.

With these 5 reports, you'll be able to quickly draw actionable marketing ideas to improve your results.

1. Conversion Rates between Mobile & Desktop

Let's get started with an easy one.

Considering that mobile internet users now outpace desktop, it's fairly safe to assume that your mobile and tablet experiences need to be as good (if not better) than the one for desktop users.

However that's a tricky proposition if there's a multi-step checkout process users are forced to navigate with their thumbs. Or 5+ form fields that are cumbersome at best when you're awkwardly typing out sentences with your fingers.

Getting clients to buy-in, or bosses to sign-off though is another matter.

Fortunately, there's a simple report buried under the Audience section in Google Analytics that can quickly show how your mobile and tablet conversions measure-up compared with desktop.

The results can provide the ammunition you need for more funds and better resources.

Step 1. After clicking on the Audience section, go all the way towards the bottom to find the Mobile > Overview.

Step 2. Now select your primary conversion goal under the appropriately named Conversions section.

Step 3. The first place to look for discrepancies between devices is in the engagement or Behavior section.

Conversions rarely happen after seeing only one page or being on the site for under a minute. So generally speaking, besides an obviously low bounce rate, you'd like to see higher Pages / Session and Average Session Duration.

Significantly lower numbers on mobile and tablet (vs. Desktop) is your first clue to a poor mobile experience.

The second, is the conversion rate number of each device. Again, higher is better generally. So a significantly lower conversion rate on mobile or tablet (compared with Desktop) should be a warning sign.

Bonus Tip: The best way to sell a fix or change is to calculate the cost of lost sales. Find the difference between sales or customer value of current Desktop and Mobile conversion amounts to provide a number of 'lost sales' that could be gained if you can make some improvements.

2. Identifying How to Improve Paths through Your Site

Most clients (and bosses) obsess over the homepage. They nitpick image selection, and shove as many things as possible into the tiny layout you provide.

Which makes sense, because it's the focal point for how the rest of the site is going to look and function. It's typically thought that it's the starting point for the brand, where users begin their journey and find out where to go next.

However that's not always the case.

If you've been creating content successfully on a regular basis, you'll probably notice something strange when you view the most popular pages on your website…

The homepage will only account for roughly ~30% of incoming traffic. The rest? Your long-tail blog topics that are picking up more informational or educational topic queries.

What does that mean? The way visitors navigate through your site is probably pretty different than what you expect (or planned ahead for).

Here's how.

Step 1. Open up the Behavior Flow underneath the Behavior section.

Step 2. Now filter or segment your traffic based on the Source/Medium it's coming through. Google/Organic will be your best bet for finding organic search visitors arriving at your site through content, SEO and other 'inbound' means.

Step 3. The first section here is your Starting pages, or landing pages / blog posts that people are coming to first from Google.

You'll see in the example above that the homepage (denoted by the forward slash “/”) only accounts for a 20-30% of total visitors. The rest are going to other pages and blog posts first.

Step 4. The next interaction is where people are going after leaving the first page of your site.

Again, you'll notice that people commonly go visit other web pages or blog posts (in addition to the homepage).

That means you have these intuitive paths' that already exist on your website, where visitors are trying to navigate or find certain things that you didn't necessarily plan out.

A quick win here includes helping people navigate (or see appropriate calls to action) more easily. Zero-in on the most common interactions or traffic flows, add new internal site links or ads to get people further down the funnel and into your macro (or micro) conversions.

3. 'Low-Hanging Fruit' Pages to Improve for Search

A few years ago, Google mysteriously stopped passing referral data to webmasters for “privacy” reasons (as if that exists on the internet).

While you could, conveniently, pay them in AdWords for this data (how nice), another way to get some quick SEO insights is to view the terms currently sending you traffic in the queries report (helpfully located under Acquisition > Search Console) sections.

The objective here though is to find all pages or terms currently ranking on the second page of Google (you know, the one nobody clicks on), improve those, and get them ranking on the first page (so they're going to actually send you traffic).

Step 1. Once you've located the Queries report, fire up an Advanced Filter. By default, Google often does a data dump into analytics, showing you tons of data at first glance and allowing you to dive deeper (if you know what you're looking for).

These advanced filters (in addition to secondary dimensions) will help you narrow down the results into something a little more actionable.

Step 2. Now sort the data to display all results with an average position of OVER 10.

(There are 10 results on a search engine result page (SERP), which means the 11th position is the first result on the second page.)

Step 3. Pull down all the results currently ranking high on the second page. This is your 'low-hanging fruit' for quick content + SEO wins.

Now your job is to simply improve these pages! Maybe that's the design aesthetic or adding some new production design to liven the page up. It could be adding content and additional context or information to make the page more in-depth. It could even be adding in new media types like videos to help explain or show what the page is talking about.

Find high potential yet underperforming pages, and improve those FIRST before going back to creating new content from scratch.

4. Top Search Pages Leaking Visitors

As we've seen so far, visitors don't always do what we expect them to. And they don't always find what they're looking for.

That's evidenced by high bounce rates, especially on important pages that are bringing in a ton of traffic to your site.

Finding those pages that (a) rank highly, (b) bring tons of traffic, but (c) fail to convert them could give you another quick boost of new leads or customers.

Step 1. Start by locating your most popular content under Behavior > Site Content > All Pages.

Step 2. Now we're going to use another filtering or sorting tool to make this information more relevant. Click on Secondary Dimension, which we'll use to again filter Source / Medium.

Step 3. Typically Google Analytics will automatically show the most popular pages. If that doesn't happen, simply click on the Unique Pageviews to show the most popular first.

Now cross-reference these super-popular search pages (yay!), picking out the ones with super-high Bounce rates (boo!).

It's common for blog posts to have bounce rates as high as 60-70%, however anything over that should be cause for concern. General website pages have lower bounce rate ranges of anywhere from 30-40%.

Much like the last tip, our goal here is to improve these pages! So many of the same tactics (e.g. adding new media types, improving design or internal linking, etc.) apply.

However you might also consider finding out WHY people are bouncing. Many times there's a disconnect or mismatch with what people were expecting to see, and the information on the page that you're delivering.

Try using some qualitative methods (like Qualaroo, live chat, or other survey pop-ups in your marketing stack) to get quick feedback on what people what to find when they hit this page.

5. Top Converting Content to Improve Internal Linking

Following the last few steps will help you identify the most popular way people are (a) arriving at your site and (b) navigating through it.

Executing those steps will help you capitalize on bringing in more site visitors while also shoring up holes or leaks causing people to leave too early because they're frustrated or can't find what they wanted.

The next logical step is to effectively funnel these people into your primary website goals or objectives to move your business metrics (like leads and customers).

Fortunately, there's a simple report buried deep that can help you connect these dots.

Step 1. Located the Reverse Goal Path under the Conversions section of Google Analytics.

Step 2. Select the primary Goal you'd like to view or analyze.

Step 3. Now you'll be able to see the previous pages people used before accomplishing this Goal on your site. That means the page or two just PRIOR to converting.

These are your highest converting (or assisting) pages that you should funnel the rest of your visitors to from the other popular pages that you've discovered so far.

Easy. Peasy.

How to Connect the Dots: Combining Kissmetrics with Google Analytics

As we've seen so far, Google Analytics is great at telling you how and where visits might be coming from; that 'top of the funnel' information that's useful in making tactical decisions about specific marketing channels.

However, it's not so great at what comes next… tracking initial visits once they transform into bonafide leads, prospects, or customers.

Google Analytics only tracks the individual session (or visit) data, which also tends to skew conversion attribution (like showing the 'last-touch' people used prior to converting, overreporting some channels while underreporting others). All information from that visit is then discarded.

They have conversion funnels, but again they're limited to both (a) only showing future data and (b) only tracking what happens on that single visit. Once the person leaves, their data does too.

That's why using it alongside a tool like Kissmetrics makes sense. They're complementary, largely because of the difference in how they handle or track visitors.

Kissmetrics will treat visitors from the same device as the same visitor for example. It also saves all of that person's previous session information (even if they didn't convert) so that you'll get a more nuanced view of what individual leads or customers actually did for the months, weeks or days leading up to a conversion.

That means your conversion data will not only be more accurate, but also more actionable as well. Below is one example of the funnel reporting showing steps to purchase.

These additional features also enable you to run more sophisticated, granular analysis of individual cohorts.

Google Analytics is great for general information (like total numbers or averages of all session data). However it also lacks the nuance to sometimes dive deep. Using it alongside a more robust tool like Kissmetrics can help you gain back the ability to view individual customer interactions (both on your website and even inside an application) and analyze conversion data with greater insight (not to mention, accuracy).

Conclusion

Wanna double conversions in a few weeks?

Don't worry about running A/B tests. And don't waste time with new page or content creation.

First, go back and fix all the stuff that's not working. The poor device experiences. The un-optimized (and unofficial) paths through your site. The high potential pages or posts hidden from the world on Google's page two. And the popular pages that people are leaving immediately in droves.

Next, connect the dots by getting people from the most popular pages and paths to your pages that convert (or assist conversions) the highest.

Raw data, by itself, is meaningless. But using these five simple reports can help you layer in context and gain actionable insight that has the power to increase leads and sales literally overnight.

And best of all, it's data-driven. So you can focus on what's important (like successful implementation) instead of getting distracted by biases or HiPPO's along the way.

About the Author: Brad Smith is a founding partner at Codeless Interactive, a digital agency specializing in creating personalized customer experiences. Brad's blog also features more marketing thoughts, opinions and the occasional insight.

Sell Like Amazon: 7 Examples of Triggered, Automated, and Personalized Marketing Campaigns You Can Set Up This Weekend

You've heard that marketing automation can help you nurture leads, increase your conversions, and grow your revenues… without spending more on advertising.

According to Lenskold Group, 63% of companies that are outgrowing their competitors have adopted marketing automation.

In the B2B world, DemandGen Report found that 67% of marketers see at least a 10% increase in sales opportunities with lead nurturing-a core feature in marketing automation tools.

It's no surprise, then, that companies are intrigued. Google Trends shows that global annual searches for “marketing automation” have been growing steadily for nearly a decade.

2007-2016 searches for “marketing automation”

And yet, when it comes to actually implementing marketing automation software, it can be hard to know where to begin.

Neil Patel sums up the challenge bluntly in his Definitive Guide To Marketing Automation:

“Here's the biggest problem with marketing automation today. It's entirely software driven with large companies producing the thought leadership. It's easy to feel lost in technical jargon.”

In this post, we'll aim to cut through the jargon and give you a defined playbook of seven automated marketing campaigns that you can set up in just a few days on any major marketing automation tool.

1. Personalized Call To Action


2. Educational Email “Mini Courses”


3. Automatic Broadcast Resend


4. Pull-Back Campaigns


5. Automatic List Pruning


6. Post-Purchase Check In


7. Warm Prospect Outreach

1. Personalized Call To Action

This hack will give you an unfair advantage over your competition.

Chances are, most marketers in your industry send the same newsletter to everyone on their list. Customers get the same content as leads. And leads get the same content as dead email subscribers.

Personalized calls-to-action flip this model on its head.

When you set up personalized calls-to-action, your recipients get email content that changes based on their stage in the sales funnel. This means that every lead gets the perfect “next step” you want them to take.

For example, let's say you're a SaaS marketer.

You could add a P.S. to your weekly newsletter that changes for leads (P.S. “Start your 14-day trial today”) and existing customers (P.S. “Learn more about our Pro plan”).

Your execution will depend on your marketing automation platform. Most automation tools with this capability let you create dynamic content with simple if-then logic. And you can often copy and paste pre-written shortcode to build your dynamic content. No coding required.

Here's what the above example would look like in your email editor using Liquid markup:

{% if subscriber.tags contains “Lead” %}

P.S. Start your 14-day trial:

{% if subscriber.tags contains “Trial” %}

P.S. Learn more about our Pro Plan:

{% if subscriber.tags contains “Pro plan” %}

P.S. Learn more about our Business Plan:

{% elsif subscriber.tags contains “Business plan}

Even if 90% of your email content is the same, personalizing your CTAs can give you a big boost in conversions.

In a study of more than 93,000 calls-to-action, HubSpot found that CTAs targeted to the user had 42% higher conversions than calls-to-action that were the same for all visitors.

If you want to increase your conversions in email, personalizing your calls-to-action (for most businesses) is low-hanging fruit.

2. Educational Email “Mini Courses”

Many marketers these days obsess over email list growth. But there might be one KPI that marketers struggle with even more than turning website visitors into subscribers.

Converting subscribers into paying customers.

According to Ascend2, B2B marketers say that the most useful metric for measuring marketing automation performance is conversion rate.

There's no “one size fits all” approach to converting email subscribers. But one way to cut through the noise in the inbox, build trust, and qualify more marketing leads is to craft an authoritative email mini course.

Email mini courses are email drip campaigns that deliver one lesson per day, usually for five or seven days, to your prospects on a topic they care about.

At Close.io, CEO Steli Efti offers a free mini course on startup sales. Naturally, subscribers who want to improve their sales also want to hear about Close.io, a SaaS platform for sales professionals.

Email mini courses also have a subtle, powerful benefit.

They train people to open and engage with your emails.

This point can't be overstated.

When you grow your list with a traditional lead magnet like a free ebook, you often find that your open rates fall off a cliff after several follow ups. The truth is, sometimes people don't expect or want to hear from you. They just wanted the free ebook.

Mini courses, on the other hand, flip this script.

In order for people to get the lessons in your course, they need to read your emails. This trains subscribers to open, click, and reply to your marketing message. And isn't that the whole point of building a lead magnet in the first place?

For B2B marketers, DemandGen Report found that lead nurturing results in 50% more sales-ready leads at 33% lower cost per lead. Try nurturing your leads with a five or seven-day automated email course, and watch your conversions increase.

3. Automatic Broadcast Resend

Imagine if you could get 30% more opens on any email you send.

That means your next webinar announcement, major product launch, or one-day sale would get 30% more email traffic.

With the Automatic Broadcast Resend hack, this is possible.

SumoMe co-founder Noah Kagan popularized this hack and summed up his ROI like this:

“1 minute of work = 7,028 more people read my email.”

Here's how you set this up:

The next time you send a critical broadcast, wait a few days, then create a new email list from the people who didn't open it.

Then just change the subject line and send the same email to the folks who missed the first one. This re-send can result in 30% more opens (and a double-digit increase in conversions) on email campaigns. And most marketers aren't doing it.

Some automation platforms let you automate this with a few clicks. If you're on a platform that does this, you can simply enter your second subject line, choose a time and day, and queue up a re-send at the same time you schedule any broadcast.

4. Pull-Back Campaigns

According to BI Intelligence, online retailers lose a startling $4 trillion per year in revenue due to abandoned shopping carts. Even worse, an estimated 63% of that revenue is recoverable.

Over the years, ecommerce companies have come to realize that cart abandonment is a problem. But fewer marketers have a strategy to address page abandonment.

Suppose someone visits your pricing, services, or demo scheduling page-then leaves without converting. They're clearly interested in your product or service. And if you have remarketing campaigns set up, your prospect will see your ads.

Remarketing can help, but according to Close.io, following up with leads within 5 minutes makes them 100X more likely to convert than following up within one hour.

That's where the pull-back campaign comes in.

Pull-back campaigns are automated emails designed to “pull” prospects back to a key page on your website, triggered minutes (or seconds) after they abandon the page.

Note: Prospects need to be on your email list for you to trigger pull-back campaigns. Technically, subscribers receive a browser cookie from your automation software (either when they first subscribe, or anytime they click through from an email sent by the tool) that identifies them as a subscriber. Then, you can set up rules to trigger email pull-back campaigns when they visit-and abandon-specific pages on your website.

Chris Schwarz from Kwasi Studios received the following pull-back campaign from Amazon several days after looking at digital cameras without buying:

When it comes to crafting your campaign, you have a few options. In general, it's a good idea to address objections that cause people to abandon your website in the first place.

You could write:

• “I lead our Search Engine Optimization team. When's a good time to set up a consultation (totally on us) about improving your organic traffic and revenue?”


• “We offer free shipping in the domestic USA. Click here to shop now.”


• “After you start your trial, we send you a reminder email before we charge you. Is there anything holding you back from trying the software today?”

Focus on giving a helping hand, and make yourself available to answer any questions.

If you have a high customer lifetime value, this campaign can drive significant ROI by reengaging “silent” leads on your website with perfect timing.

5. Automated List Pruning

You know those subscribers on your email list who never open your emails?

They're probably hurting your business more than you think.

Here's the truth about inactive subscribers:

Low engagement hurts your deliverability across the board.

Here's how Unbounce sums up the problem:

“ISPs will look at who you are sending to, how often, the number of abuse complaints from sends and whether email is opened or clicked on. All of these factors determine your reputation with your ISP and affect whether your emails are delivered to your subscribers' inboxes.”

Here's the key phrase:

“ISPs will look at… whether email is opened or clicked on.”

This means that, even if people aren't marketing your email as Spam, simply not opening your email can hurt your deliverability to even your most engaged subscribers.

The solution is to add a trigger that automatically tags folks who haven't opened your past 10 emails. From there, you can send them to verify that they still want to hear from you.

Crunchbase does a great job with their automatic verification. This keeps their list clean and their deliverability high for all subscribers.

Again, your implementation will depend on your automation tool. Some platforms have built-in pruning operations, which make it dead simple to clean your list with one click.

With other tools, you'll have to manually execute this-but the ROI is worth it.

6. Post-Purchase Check In

This campaign is simple. And deceptively powerful.

After you pick up a new customer, at minimum, you should send a goodwill email 14 days later that says, “hey, it's been 14 days-I just wanted to check in and see how it's going for you.”

The check-in email has become common in SaaS. But in other industries-like ecommerce, online courses, and consulting-it's shocking how few businesses follow up with customers and ask if they're enjoying their purchase.

Sean Fioritto, author of the ebook Sketching With CSS, used the post-purchase check-in to campaign generate over 100 testimonials for his ebook.

When readers buy the ebook, Sean's automation software waits 14 days after the purchase, then triggers the following email:

Hey,

You picked up a copy of Sketching with CSS a couple weeks ago. One of the advantages of buying a book directly from the author is, well, me. :- )

I respond to every email and I love hearing from readers.

So how's it going so far?

When Sean gets positive replies, he simply replies and asks for permission to use people's quotes as testimonials. Most customers are fine with this. And they give Sean all the social proof he needs for future marketing campaigns.

According to Marketing Metrics, “the probability of selling to an existing customer is 60 – 70%, whereas the probability of selling to a new prospect is 5-20%.”

Use the post-purchase check-in campaign to nurture your customers and set the stage for repeat business. This one should take less than an hour to set up.

7. Warm Prospect Outreach

Are you using lead scoring at your company?

Lead scoring separates marketing automation tools from traditional email marketing software. Lead scoring assigns a score to contacts in your database, based on their behavior (such as opening and clicking emails, email inactivity, visiting your Pricing page twice in one week, downloading guides, or just about any other action you can track with a piece of JavaScript on your website).

When a contact reaches your pre-defined lead score (say, 100), you can trigger actions.

Depending on your business, you might want to take hot leads and:

• add them to your CRM and assign them to a team member


• move them to a sales-focused drip campaign with case studies


• Move them to a campaign that syncs with Facebook custom audiences

The possibilities are endless.

You can also send an automated direct outreach email, like Beachhead.io:

The email Beachhead.io triggers when you download several whitepapers.

Beachhead, a consultancy, uses lead scoring to reach out to high-value prospects who consume their content. If someone downloads five of your six whitepapers and views your pricing page in one week, you can bet they're interested in your product or service.

Lead scoring lets you automate your direct outreach emails, so they engage warm leads even while you're not working.

Conclusion

More and more, marketers are moving away from the “email blast” and sending more targeted, relevant, and automated emails.

According to Ascend2, 76% of companies in 2016 say marketing automation is “very important” to their overall marketing performance (up 11 percentage points from 2015).

The problem for most marketers is that marketing automation can be confusing.

While social media and content marketing are highly visible, marketing automation often works in the background, making it harder for marketers to study.

With the 7 campaigns above, you should have a better idea of what's possible, and some concrete steps to increase conversions and automate your marketing.

About the Author: Rob Walling is an angel investor, podcaster, author, and serial software entrepreneur who most recently started Drip, a lightweight marketing automation tool. You can follow him on Twitter @robwalling.