Search engine optimization (SEO) is a fairly forgiving online marketing discipline. It’s a long-term strategy, so if you make one mistake, you’ll usually have plenty of time to correct it.
However, there are some important lessons every SEO practitioner must learn early on.
1. Don’t try to outsmart Google.
First, understand that you’re never going to outsmart Google. SEO is about understanding Google’s algorithm and working within it to provide better content for your visitors and, hopefully, earn higher organic search rankings in the process. If you try to find loopholes in that algorithm, or rely on “black hat” tactics to inch your way up the rankings, it’s only going to work against you in the long run.Too many newcomers believe they can get away with tactics like spamming links or stuffing keywords, but it never works for long; Google’s quality indicators have always been good, and they keep getting better, which means even if you get away with a tactic now, you probably won’t get away with it later – and you may find your website with an algorithmic or manual ranking penaltythat can be exceptionally difficult to recover from.
2. The same strategy won’t work for everyone.
Let’s say you’re working with a single client, and you have everything in order. You’ve picked the right keywords, you’ve developed great content, and you’ve built great links to see fast growth. Now you acquire a new client, with a different brand and a different audience. Do you use the same strategy?
It’s tempting for SEO newcomers to copy and paste the same approach, but this is inadvisable; your clients (or employers) will have different goals with their SEO campaigns, different competitors, keywords, and other variables, and may respond to different variables in strikingly different ways. Learn from your past strategies, and use elements from them in your new campaigns, but avoid trying to replicate any strategy in its entirety.
3. You have to change how you talk about SEO.
The more familiar you become with SEO, the deeper your technical knowledge will become. You’ll have an internal dialogue (or a dialogue with your peers) that freely uses terms like “robots.txt” or “meta data” like everyone knows what you’re talking about. But when you report your results to a client, or a boss who doesn’t understand the technical side, you’ll have to learn to talk about these technical factors in a way that makes sense to a non-SEO-expert.
Spend some time preparing to talk in this other level of language.
4. People don’t always search the way you expect.
When you start brainstorming keyword ideas, it’s a good idea to put yourself in the mind of the average searcher, imagining what words and phrases they might use to find a brand like yours. You may also use keyword research data to indicate which keywords are potentially most valuable for your brand. These are sound strategies, helping you both quantitatively and qualitatively predict how your users might search in the future.
But you should know that users don’t always search the way you’d expect them to; prepare to be surprised, and to adjust your campaign as you learn what your users are really searching for.
5. Only trust what you can measure.
You may think you have an amazing piece of written content, but how much traffic is it attracting? How many comments has it encouraged? You may think you’ve built a high-quality link, but how is it impacting your domain authority? How much referral traffic are you getting from it?
Even though you might feel like you’re developing an instinct for how campaigns develop (especially in the later stages of your career), it’s better to only trust what you can objectively measure.
6. Audit and reevaluate everything periodically.
Just because a strategy worked for you last year doesn’t mean it will this year. Things change too quickly, from the nature of the algorithm that drives how Google search works to the consumer preferences that drive search patterns. Accordingly, you’ll need to regularly reevaluate your tactics, determining whether they’re still worthwhile and finding opportunities to improve. I recommend doing a full sweep of your approach annually.
Monthly check-ins, when you report on results, are also a good idea, to spot high-level issues or successes in time to respond quickly to them.
7. Reading and talking is the only way to stay up-to-date in this fast-moving industry.
Remember what I said about things always changing? Early in your career, you’ll learn that to stay relevant, you need to plug yourself into the community. You’ll need to read relevant publications, and talk to other people like you on a regular basis if you want to stay relevant and up-to-date with the latest strategies. If nothing else, you’ll get helpful tips—and proactive words of warning if you’re taking the wrong approach.Are you familiar with these SEO principles? Good. You’re going to need them if you want to be successful. Though you’ll have many years to correct your behavior and accumulate assets like content and links to improve your campaign, if your underlying SEO philosophies are out of order, you may never achieve your true potential as an SEO ninja.
Is one or your clients about to split? Here are some common reasons clients decide to fire their SEO agency and actions you can take to prevent it.
The agency-client relationship can be fragile.
This can be especially true of SEO agencies, given the long-term commitment required to see optimal results. A lot can change during that time and, sometimes, a client decides it would be best to part ways.
However, this really doesn’t have to be the case. There are some predictable, avoidable reasons clients decide to split with their agency.
I spent more than seven years working at digital marketing agencies and learned (sometimes the hard way) to sense when clients were unsatisfied. There were some common patterns that played out over time.
The good news? A bit of honesty, clarity, and some positive results can save your agency-client relationship.
Here are five reasons clients choose to fire their SEO agency and some actions you can take to avoid getting fired.
1. “We Can’t Implement Your Recommendations”
SEO is fundamental to increase visibility, but it is harder to achieve this if you don’t control the website. As a result, hefty tomes filled with SEO recommendations can end up gathering dust in the client’s inbox.
With some larger clients, I’ve seen thousands of technical recommendations go unimplemented. The clients’ (quite valid) argument has been that these only have a value as they relate to website improvements. Without seeing the light of day, the recommendations are essentially worthless.
There are numerous reasons why this occurs. If the client isn’t in a position to give the agency direct access to the site, it usually means going through a web development queue every time a change is suggested. Should other recommendations take precedence over yours, you may find that SEO gets lost in the crowd.
How to Avoid This:
- Present a business case for your recommendations. Communicate, in terms everyone can relate to, why it’s good for the client’s business to follow your team’s advice.
- Get to know the hurdles your client faces when implementing SEO updates. Work together to overcome them.
- Set targets for everyone. It takes a team effort to improve a site for SEO, so it’s worth creating a dashboard to track how many changes have been seen through and where the bottlenecks are. This helps to quantify and visualize any issues.
- Build relationships with senior leaders at the client’s business.Sometimes the client requires an organizational change to get SEO bumped up the priority list. Without senior-level approval, that is unlikely to happen.
- Add a caveat in contracts (in some cases). This can state simply that should the agency’s SEO recommendations not be implemented within a reasonable time frame, any agreed performance targets need to be revised.
2. “SEO Isn’t Delivering Like Our Other Channels”
The gift and the curse of SEO can be its long-term effectiveness as a performance channel. In theory, everyone is on board with the fact that SEO takes longer than PPC to bring positive returns.
In practice, it’s easy to grow impatient when you see how SEO stacks up against PPC or even paid social in the immediate short term.
The agreement between agency and client about how long SEO takes to work becomes particularly fraught if things start to trend downwards. Even a slight week-on-week dip in visibility can be cause for concern.
To marketers accustomed to paid search, it can be difficult to shift mindsets and accept that there are rarely instant fixes in SEO. Barring a serious technical problem, in SEO these dips can’t be reversed so readily. They must be put into a wider context and investigated in detail before actions are taken.
How to Avoid This:
- SEO isn’t supposed to deliver like other channels, so the best way to avoid this scenario is to work on developing trust in your approach. Set expectations appropriately at the outset and provide frequent updates.
- Make sure your team identifies any performance changes. If the client notices it first, you can seem either negligent or keen to hide something. If you feel the client may be concerned with what they see, get in touch first to allay any fears.
- Offer to educate your client’s team if they aren’t so familiar with SEO. Clients are usually open to learning more about digital marketing.
- If things simply aren’t turning out like you thought they would, be honest. Performance won’t improve without everyone getting on board with a new approach. That starts with an up-front conversation about what’s gone to plan, what hasn’t, and what you need to do to turn things around. Clients appreciate a bit of integrity more than anything else.
3. “We’re Not Sure What We’re Getting for Our Money”
A lot of SEO work goes on in the background. We spend a huge amount of our time analyzing trends, identifying opportunities, and preparing documents.
We have to put this time in if we want to compile an effective strategy. However, the client rarely sees this. Our processes can be hidden, with only the outputs to show.
Some clients have had a bad experience with an agency, too. I’ve seen plenty of clients approach a new agency with a paid link penalty in tow. It’s understandable that this causes a certain guardedness about SEO agency practices in general.
If we keep our processes out of sight, that skepticism will only increase. From there, the relationship is hard to retain.
How to Avoid This:
- Spend time going through your statement of work with the client. Make sure they understand what each item is, how long it will take, and why you think it’s the best use of their budget. That way, there should be no surprises and they are free to amend things as they see fit.
- Stick to your project plan. If there are any deviations from this, discuss them with your client and confirm the changes in writing.
- Use a shared project management tool like Basecamp or Teamwork. This provides visibility into your team’s daily tasks and helps to assign items to the client, too.
4. “You Haven’t Delivered on Your Promises”
This one stereotypically befalls the salespeople who promise incremental, oftentimes stratospheric, improvements in performance — up and to the right to infinity. This can help get the sale, but then it’s the SEO account team that has to make good on the promise of triple-digit growth.
However, this isn’t the exclusive domain of the over-eager salesperson.
We can all get a little carried away just through the desire to please a new client.
This can leave us with performance targets that loom large on the horizon once the honeymoon period is over.
Additionally, this applies to the account team you provide for the client. I’ve seen agencies put forward an account team in a pitch document, then deliver an entirely different set of people once the ink dries on the contract. This makes the client feel like they are being taken advantage of from day one.
How to Avoid This:
- Make it clear what exactly is being promised to a client. Performance projections, for example, can be viewed as legally binding. Clients can feel that they are buying that traffic by signing with your agency. Your methodology for calculating a forecast (if you do decide to supply one) and all caveats to this must be provided in a transparent manner.
- As an agency, it is essential to have a clear code of conduct, both internally and in your interactions with clients. Make this explicit in your initial written agreements with a client so they feel assured that you’ll stick to your word.
- Let your client meet their account team during the pitch phase. Often, an agency will send their best salespeople to try and seal the deal, but all the clients I’ve met really want to meet the people who will be working on their account.
5. “We Feel Like We Can Take It From Here”
“What will your SEO agency provide after month three?” Many clients have been asking this question of their agencies lately.
The perception is that the heavy lifting of technical SEO and on-site implementations will be done within this period. After that, surely it’s just about occasional maintenance and some reporting, right?
This can lead some clients to feel like, after they’ve received the initial audits and strategy documents, they’ve got all they need from an SEO agency. Basically, they think they can “take it from here.”
We know they’re wrong (obviously). But the onus is on us to make the case.
An SEO specialist can add to any conversation that relates to a client’s website. This is as valid in month 12 of the contract as it is in month one – perhaps even more so.
Our efforts have a cumulative effect. SEO practices provide more value through their application over time. This applies to our technical SEO work, content marketing, and digital PR.
The full impact of our work is lost if the relationship is severed after just a few months.
How to Avoid This:
- Provide case studies that show the positive effect your SEO team has on a client’s business over time. This should demonstrate that you need at least six months to make a real difference.
- When preparing a service-level agreement, make reference to specific time frames. Clients may feel that they are getting everything up front, but some of our work only really kicks into action in month four or later.
- A lot of clients have good reasons for believing they can take up the mantle from their agency. Perhaps they have hired an in-house SEO specialist, for example. In this case, offer to transition your activities over to their team and make sure the client is in the best possible shape for success.
Learn how machine learning and automation are empowering search marketers today and how it can tackle digital marketing’s data problems.
Advertising has changed a lot over the years.
There was a time when machine learning, automation, and software-based marketing tech stacks weren’t a “thing.”
But now we’re past the days of just radio, outdoor, print, and a handful of channels on TV.
There are hundreds of channels across physical and print media and online at present, including social, mobile, and video. Even TV has diversified into hundreds of cable channels on your remote control. And yet, digital ad revenue has gone on to surpass that of TV.
The dominance of digital is nothing new. Paid search marketing is becoming more data-focused than ever before.
In fact, if you check the folders on your computer, I’m guessing some of you will find a few million-row spreadsheets full of cost-per-click bids, conversion rates, and return-on-ad-spend figures – along with countless other metrics for however many thousands, or millions, of keywords you manage.
So, What Do You Do with Big Data?
Because paid search is so reliant on big data – really big data, the kind that causes Excel spreadsheets to eventually crash for having too many rows – it’s my belief that the future of digital is inextricably tied to machine learning.
Is it because machine learning, automation, and software will completely replace savvy digital professionals and their creative ideas?
No. Far from it.
I believe that the future of digital will be a combination of smart marketers – like yourself – empowered by smart automation based on machine learning. As it happens, in a survey we recently ran on the subject, 97 percent of top digital marketing influencers (including speakers from AWeber, Oracle, and VentureBeat) agreed.
What Is Machine Learning & Why Is It Important?
Machine learning is the smart automation that can parse those million-row spreadsheets and pull valuable insights out of those mountains of data.
(To clarify, processing data to pull insights is something machine learning can help with… but actually taking those insights and doing things that are creative and smart with them? That’s still very much the domain of brilliant marketers like yourself, and why the ingenuity you bring to the table will continue to be so important when facing tomorrow’s digital challenges.)
As for why machine learning is important? For starters, digital advertising has a data problem. In addition, the face of marketing is changing due to the way your customers are becoming aware of, considering and purchasing your goods and services.
Digital’s Data Problem in Three Parts
Data is a challenge in modern marketing. There’s significantly more of it than there used to be, and as marketing technology matures, it becomes capable of collecting even more on top of that.
Data overload is a known problem. There’s too much of it – an overwhelming abundance of it already.
Yet Oracle points out that digital data growth is expected to increase globally by 4,300 percent by 2020. This problem isn’t going away anytime soon.
Despite the collection of data increasing exponentially, there’s a lack of centralized ownership with big data. You and your colleagues may be collecting CPC, CTR and CVR data in spreadsheets, but is everything centralized and standardized in a way that everyone in your organization can pull the data when they need?
Veritas reports that 52 percent of all business data is “dark” (of dubious or completely unknown value), and projects that mismanaged data will cost businesses $3.3 trillion by 2020.
There’s also a problem with siloing. Most businesses collect data in different buckets that aren’t necessarily integrated directly with each other, or indeed, with their own in-house marketing tech stack.
Accenture reports that while three-quarters of all digital skills gaps (the gap between a team member’s current level knowledge and the level of knowledge they need to successfully use new tech and tactics) come from lack of ownership, the remaining 25 percent of digital skills gaps come from a lack of integration.
And Then There’s the Changing Customer Journey
In addition to changes in the way data is collected and used in digital advertising, customer behavior is changing.
Advertising isn’t limited to a handful of channels. There are literally thousands of ways to reach customers, and pretty much all of them can be easily tuned out by an audience of increasingly demanding and disaffected customers who expect to have exactly what they’re looking for delivered to them instantly (and who will react poorly when it isn’t).
Research firm McKinsey breaks down the all-important consideration stage of the buying journey into four parts: “initial consideration; active evaluation, or the process of researching potential purchases; closure, when consumers buy brands; and postpurchase, when consumers experience them.”
The firm also finds that two-thirds of the touchpoints in the crucial evaluation stage are customer-driven, including browsing online reviews or soliciting word-of-mouth recommendations.
More to the point for those of us in digital, the use of ad blockers has increased 30 percent in the past year. And as you’ve surely heard, Google itself will be building in an “ad filter” in a 2018 version of Chrome to filter out “irrelevant” and “annoying” ads.
Effectively, as time passes, your ads are at greater risk of being filtered out by users who aren’t buying what you’re selling at this exact point in time.
How Does Machine Learning Solve These Problems?
Machine learning can be used to rein in the challenge of data, particularly when combined with disciplines such as probability-based Bayesian statistics, regression modeling, and data science. One of its greatest strengths here is the ability to take data-driven insights and build predictive models.
These predictive models can, in turn, be used to proactively address points of peak buying interest, attrition, or other key moments observed in the customer buying journey.
Examples of Machine Learning in Action
Let’s look at some examples of the way this technology is being used.
Chatbots & Voice Assistants
You may have noticed an increase in the use of conversational interfaces from major publishers such as Google, Amazon, Microsoft, Apple and Facebook in the form of chatbots and voice assistants (Alexa, Google Assistant, Siri and Cortana among others).
TOPBOTS notes that chatbots can have uses in unique, consumer-based contexts, such as event ticketing, health-related questions and the ever-important sports scores. These interfaces create a relevant and engaging user experience by supplying conversational responses based on historically-collected data – the most commonly-used or highly-searched terms.
Predicting & Preventing Customer Churn
A significantly deeper-funnel strategy at the post-purchase stage is to use machine learning to forecast common points of customer attrition.
Microsoft Azure and Urban Airship have both built predictive analytics models to determine the approximate timeframes and buying stages at which customers tend to most frequently churn. By projecting these important points in the future, these businesses are then able to proactively address common complaints before customers churn, driving higher retention and ultimately strengthening their businesses.
Natural Language Processing (NLP) and Semantic Distance Modeling
Another method of using machine learning specifically for digital advertising is to predict accurate bidding models for low-data keywords, such as long-tail keywords with high purchase intent but little to no empirical data.
In these cases, machine learning-based digital advertising solutions can assign new keyword groups based on semantically similar keyword groups and help advertisers ramp up long-tail keyword groups and all-new ad groups with a minimum of expensive testing time.
Machine learning isn’t necessarily a threat to marketers. On the contrary, it’s a powerful ally that’s making marketers’ lives easier while empowering them to predictively engage their customers in a highly relevant way.
Now, more than ever, it’s important to deliver the right message to the right customer at the right time – and with the power of machine learning, marketers are able to more accurately accomplish this goal by relying on actual data, rather than guesswork.
Things you LOVE are made with CODE. Less than 1% of girls study Computer Science; I want to make a difference in changing that statistic. From fashion, film, technology, etc. things you love are Made with Code.
– Some statistics to think about-
-In the United States, 74% of girls express interest in ScienceTechnology, Engineering, and Math (STEM) in middle school.
-In high school, only 0.3% girls plan to major in Computer Science
-Computer Science jobs will be the highest paying sectors over the next decade, paying almost $15k more than average.