DSC_0291 Zach Doty Cover Photo for Installing SQl Software PostgreSQl and pgAdmin

Downloading, Installing and Getting Started with PostgreSQL and pgAdmin

How to Download, Install and Get Started with PostgreSQL & pgAdmin, Popular SQL Programming Software



Welcome back to the grand SQL journey! If you missed the beginning, here’s my previous post as a complete beginner to SQL. In this post, you will:

  • Learn what pgAdmin is
  • Become familiar with the program and some of its release history and
  • Walk through an installation of pgAdmin.


What is the pgAdmin SQL Software all about?

According to the educational material I’m working through, it’s commonplace (in some circles) to use a graphical user interface (GUI) when working with a SQL engine. (Compared to working with command line, zoinks!) That being said, pgAdmin is reportedly one of the most popular interfaces for PostgreSQL, the SQL engine / platform of choice listed out in the previous post. For the purposes of our education, I’ll be working in pg Admin 4.


Installation of PostgreSQL and pgAdmin

Here are the steps:

  • Install PostgreSQL and pgAdmin through their default Windows install methods. (Sorry Mac and Linux users, this party is PC only for now!)
  • Download a .tar file to be used for sample learning
  • Use the .tar file to restore a database we’ll be working with


Downloading PostgreSQL

First, head to https://www.postgresql.org/ in a new tab or window. When you’ve arrived, you should see something like the below screen, and click the “Download” link in the navigation.


After arriving at the Download page, you should see the below. Under the “Binary Packages” for pre-built packages, select your appropriate operating system. Windows is shown below for the purposes of this demonstration. If you feel led or qualified to choose the source code option, you probably don’t need to be reading this article anyway. 🙂


Following the Windows link should take you to the Windows Installers page.  Under “Interactive installer by EnterpriseDB, click the “Download the installer” link. Another option for “Graphical installer by BigSQL” exists, but there have been some anecdotes of annoyances with the BigSQL experience.


Clicking on the link illustrated above should take you to the EnterpriseDB site, where a screen like the below should appear. When you first arrive, you will be prompted to select a version of PostgreSQL and your machine’s operating system details. Below, I’ve selected PostgreSQL 9.6.1 and Windows x86-32, because I’ve got a really old laptop! A quick note on the PostgreSQL version selection, you should choose the latest non-Beta version to install. As this post regards software and tech, it could quickly become outdated. When you have selected the appropriate details, click the ever-important “DOWNLOAD NOW” button.


After the .exe file downloads, open it, allow it to run. A screen for Microsoft Visual C++ Redistributable will likely appear, let it run and complete. Next, the PostgreSQL installation dialogue should appear. (Below.)


Accept the default installation and data directories, unless you have a weird and specific reason to do something else. After you do this, enter your desired password.

A quick and necessary aside. Please follow best practices for passwords and information security. It is your sole responsibility to do so: protecting your information and yourself. I accept neither liability nor responsibility, nor in whole, nor in part, for your password security. Be smart.

Okay, with that out of the way, proceed to the Port portion of Setup. Accept the default and proceed. After the port screen comes a locale configuration. Accept the default and proceed. Now, you should be to start the installation process. Click “Next >”!

Once you click install, you should see a pretty traditional installation progress screen that creates a ton of directories, unpacks HTML files, and so on. (Note: this took my machine 5 minutes or so to install.) If you care to do so, uncheck any mail subscription offers and finish the installation!

From here, you should be able to get to pgAdmin 4 from your Windows start menu. Tah-dah!


If you expand the servers icon, you ought to see something along the lines of PostgreSQL9.6. If you click to expand the PostgreSQL 9.6 item, you should be prompted to enter your password. From there, you should see a dashboard with some various charts becoming populated, like below.


Next, a sample database will be restored. As shown below, please right click “Databases”, then mouse over the menu item “Create” and click “Database”.


From there, name your database and save it! Once it’s successfully created, you should see a new part of the tree for your database, with options underneath such as Casts, Catalogs, Event Triggers, Extensions and so on.


To restore data into the database, right click the database name and select the restore option. First time users, you may see a dialogue box saying, “Configuration Required”. No worries here, we’ll get through that momentarily. Click File > Preferences > Paths > Binary Paths.


Once you’ve reached the point as described and shown above, you’ll need to open a new Explorer window. (Sorry, Mac and Linux folks, no guidance from me here.) Go to Computer > Program Files > PostgreSQL > 9.6 > bin. Copy the address and paste into the pgAdmin PostgreSQL Binary Path, click OK.


That should now allow you to restore a database. Now return to the above steps, and when you select restore, select the options as desired. You should see a processing dialogue and success message. When this is complete, right click the database name and select “Refresh”. Very important – think of like you needing to refresh the data sources when working with pivot tables in Microsoft Excel.

Okay, you should have your first database! right click the database name and select “Query Tool”. Let’s make our first SQL query FTW!


In the code window, type:

SELECT * FROM [table “” not found /]

Then, either select the lightning bolt and execute + refresh. Or, you could just press F5 and it accomplishes the same thing. If the query is successful and you didn’t misspell a simple table name like I did the first time, then you should see the table in the Data Output window.



Alrighty! How about a rip-roaring start into SQL? Excited to keep learning with you. Stay tuned. If you’re just arriving at this article, here’s my running list of articles that detail how to learn SQL.



DSC_0079 Algo trading cover image by Zach Doty

MetaTrader4 (MT4) Software: A Beginner’s Algorithmic Trading Platform

Before we begin, you’ll notice this post deals with finance and investing, both of which are highly risky. This site and this post is strictly educational. Nothing in this post or on this website is intended as, nor should be construed as investment advice. Kindly first visit the Disclaimers page before you proceed, taking careful note of CFTC Rule 4.41 regarding hypothetical performance. Further, investing and trading is extremely risky, to the point that 90% of participants rapidly fail. As such, your participation in investing and trading could lead to loss of principal, and even further losses beyond that in some cases. Neither this site in its entirety, nor this post, nor any portion thereof, nor any resulting discussion or correspondence related to this site and post, is intended to be a recommendation to invest or trade mutual funds, stocks, commodities, options, or any other financial instrument. I will not accept any responsibility for any losses which might result from applications of ideas expressed on this site or in this post from the techniques or systems mentioned on this site or in this post. Nothing shown is the result of an actual trade. Neither past actual performance, not simulations of performance assure future results, profitable or otherwise.

Introduction: Why MetaTrader 4 (MT4) as a Beginning Algo Trading Platform

Alright! With the obligatory legalese out of the way, my journey into algorithmic trading and quantitative finance continues. Obviously to trade, you need to have a vehicle for doing so. Unlike the days of old where you would call a stock broker, most trading today is electronic. For many electronic trading use cases, you need:

  • A platform that at a minimum provides an electronic order management system connected to a broker
  • Who then deals with an exchange (Chicago Mercantile Exchange [CME], New York Stock Exchange [NYSE])
  • That eventually attempts to fulfill your request and back.

There are tons of software platforms and configurations which can be used to design and develop an algorithmic trading program. For the purposes of this education, MetaTrader 4 was selected as the starting platform. Though I’ve dealt with some other programs in the past such as NinjaTrader, yes, Robinhood (sigh), and TD Ameritrade’s ThinkorSwim, MT4 is the platform for this foray.


  • Free (Obviously an important reason! Other platforms offer free trials, but with limited functionality.)
  • Free data (Close second for the most important reason. If your industry is remotely related to technology, you understand data is the new oil. While some vendors may provide free end of day data (E.g., Kinetick), what you need often has a price or cost associated with it. MT4 will offer viable free and live data, helpful to the beginner.)

For Mt4, we will get free live data from the Broker. Additionally, historical data is available from MetaQuotes and other online sources like Dukascopy.

  • Access to different markets (With some footwork, we can test and trade FX, Equities Indices, Equities (Stock), Commodities and Fixed Income instruments.
  • Ease of learning the coding language (The MQL4 language is largely based on the widespread C++ programming language. In addition to its popular base, MetaQuotes Language (MQL4) is well documented with lots of users, so many examples to learn from!)



  • Lowest bar timeframe is 1min (If you’re doing more precise or higher frequency trading, this can be a drawback. However, A), we’re not doing HFT, B) if we were, there is a workaround. And we probably would some kind of integration with Rithmic for HFT-esque executions.)
  • Portfolio backtesting doesn’t come out of the box (If you’re simulating a multi-instrument algo strategy (Or in MT4 terms, Expert Advisor [EA]) you’ll be out of luck, and would have to test on another platform or find another methodology.)
  • Advanced statistical analysis doesn’t come out of the box either (It can be difficult to incorporate heavy statistical apparatuses in the algos. However, we can carry out statistical analysis on the data using Microsoft Excel or other statistical software (Python libraries, etc.). Performance analysis can be done using 3rd party software, more on that in the later.)



Other Possible Trading Software Platforms


Various reasons the above platforms listed aren’t being used includes, but not limited to:

1) Cost

2) Difficulty of learning the coding languages

3) Complicated user interfaces

4) Backtester and/or optimizer not included.

5) Software platform not well designed for building and trading algo strategies.

6) Limited access to markets

7) Poor community support and documentation


Why not MT5?

The main reason MT4 is being used over MT5 is because most brokers support the former but not the latter.

Some key differences between MT4 and MT5:

1) Different coding language (MQL4 vs MQL5). MQL5 is more difficult to pick up for beginners.

2) MT4 has been around longer and has better online support. There are many code libraries, templates and examples for MT4.


3) MT5 does not allow external data import (This is unfortunate- data management is a huge component of backtesting.)


Final Note: Why Forex as a Trading Instrument?

Convenience: Forex data isn’t (as) affected by many common market variables such as stock splits, futures contract roll-overs, expiries and dividends, etc. These factors can greatly complicate the testing and data cleaning process.

Data is available: Free data everywhere! Data on other instruments is much harder to obtain.

Can often extrapolate to other instruments: Algos built on forex can often be easily modified to fit CFDs on other instruments.

Principal instrument traded on MT4.



Thanks for tuning in- if you’re weird enough to like this, you might find my beginner’s foray into SQL interesting as well. Cheers!

Zach Doty Photograph DSC_0018

Getting Started With Algorithmic Trading

One Introduction to Quantitative Finance, via Algorithmic Trading

Before we begin, you’ll notice this post deals with finance and investing, both of which are highly risky. This site and this post is strictly educational. Nothing in this post or on this website is intended as, nor should be construed as investment advice. Kindly first visit the Disclaimers page before you proceed, taking careful note of CFTC Rule 4.41 regarding hypothetical performance. Further, investing and trading is extremely risky, to the point that 90% of participants rapidly fail. As such, your participation in investing and trading could lead to loss of principal, and even further losses beyond that in some cases. Neither this site in its entirety, nor this post, nor any portion thereof, nor any resulting discussion or correspondence related to this site and post, is intended to be a recommendation to invest or trade mutual funds, stocks, commodities, options, or any other financial instrument. I will not accept any responsibility for any losses which might result from applications of ideas expressed on this site or in this post from the techniques or systems mentioned on this site or in this post. Nothing shown is the result of an actual trade. Neither past actual performance, not simulations of performance assure future results, profitable or otherwise.

Why Am I Writing This?

Similar to my Absolute Beginning Steps for Learning SQL, I’m embarking on a number of education journeys in 2017. Another journey, seen here, is algorithmic trading. Loosely known by several monikers (below), this is an intensive field that may be both challenging and rewarding. As self-accountability and sharing, I’m posting what I learn as I progress.


What is Algorithmic Trading? (AKA Automated, Quantitative or Systematic Trading)

Put simply, algorithmic trading (quantitative trading) is trading financial instruments via computers, through logic, programs and preset conditions.


Types of Algorithmic Trading

For the purposes of this post, there are two types of algorithmic (algo) trading. 1) High frequency trading (HFT), and, 2) Low frequency trading.

High Frequency Trading (HFT): Speed is the absolute and expensive edge. Co-located servers in New York and Chicago run proprietary code on custom computer hardware, relying on fiber and microwave communications for trading movements that happen in less than a second. Having tried a variant of HFT in 2016, saying HFT is difficult is probably the understatement of the decade.

Low Frequency Algorithmic Trading: What my educational journey is going to focus on. For low frequency algorithmic trading, the trader is the edge, further demonstrated by the trading model(s) and strategy or strategies he/she designs, executes and manages.

Taking a step back, if algorithmic trading is computerized via programs and preset conditions, what main kinds of algo trading logic are out there?

Types of Algorithmic Trading Logic

  1. Macroeconomic news (Examples: Non-Farm payroll reports, FOMC policy minutes, Federal Reserve Beige Book releases)
  2. Fundamental analysis of a financial instrument (Revenues, Earnings releases, Inventory reports, Supply/demand reports, Free cash flow)
  3. Statistical Functions (Correlation, Cointegration, Mean reversion)
  4. Technical analysis of a financial instrument (Moving averages, Stochastics, Relative Strength Index (RSI))
  5. Market Microstructure (Order flow, volume profiling)

3 Core Values for Developing Algorithmic Trading Robots

  1. Market-Prudency (Ideas are fundamentally sound from a market and economic perspective.)
  2. Mathematical Models (Models and strategies are based on sound statistical methods, to maintain positive expectancy and reduce risk of drawdown and loss of capital as able.)
  3. Low Frequency (Trading frequency of the models and strategies are less than one trade per minute. Thus, the strategies do not depend on the speed or computing capacity of computer hardware and/or software.)

Goal: design and execute algorithmic trading models (robots/strategies) using basic software and hardware that average retail traders can afford.

3 Crucial Tranches of Knowledge for Successful Algorithmic Trading

  1. Tools (Trading software platforms, Brokers and execution infrastructure, Coding languages and skills, Performance analysis)
  2. Data (How to access sources, manage, cleanse and use data for algorithmic trading strategies.)
  3. Design Theory (Combining statistics, finance into focused tasks of product development and management.)

Starting Tools

As I start out on this educational journey, I’ll definitely be using the tools below, of which I have no commercial interest in. There may be more tools down the road, but that’s it for now.

  • MetaTrader 4
    • MQL4 language
  • Microsoft Excel
A scenic shot of Palo Duro Canyon from a hiking trail.

Starting SQL from the Absolute Beginning

What is this?

To be honest, I haven’t done much blogging or writing lately. Life (read: work) happens, and it gets busy. However, I’m feeling invigorated with a strong desire to expand my horizons. One such manifestation (snooze, I know) of this is to learn a bunch of new things, for where technology and industry are headed.

Thus, I present to you, learnings on SQL from a course I’m taking! Frankly, this should be boring to a majority of people. However, this is a way of self-accountability, and sharing what I learn along the way about Structured Query Language (SQL) programming, and hopefully how it applies to a bunch of awesome things! If you haven’t bounced already, here we go.

Square 0: What are Databases?

As the title/URL describes, I’m starting from an absolute beginning. While I have a range of experience (or lack thereof in some cases) with HTML, CSS, JavaScript, PHP, Regex, etc., I am completely new to SQL. That said, this isn’t square 1, but square 0.

Databases are systems that allow users to organize and store large amounts of data. Databases can have a wide variety of users and use cases. Potential database / SQL users include analysts in marketing, business or sales. Additionally, technically-focused personnel such as data scientists, software engineers and web developers may also use databases for a range of purposes.

Discussing the Transition from Spreadsheets to Databases

Many practitioners in business have some familiarity with a spreadsheet program, such as Microsoft Excel, Google Sheets or Open Office.

Spreadsheets are often useful for a one-time analysis piece or quick charting, particularly with small data set sizes. Additionally, usage of a spreadsheet program ensures that a wide range of folks with varying expertise can access, use and manage the spreadsheet data.

So where do databases come in? Databases are great for ensuring data integrity and/or handling large & robust data sets/ Databases are also great for use cases where you need to quickly merge different data sets or automate actions with your data for frequent usage or re-use. Additionally, databases are widely used in powering websites and other applications.

In summary, the transition from spreadsheet to data comes when you bring massive amounts of data to life! The hope of the educational materials are that institutional knowledge in spreadsheets can be leveraged to help understand and master SQL database usage.

What are some quick hacks to translating spreadsheets to databases? The first is that tabs of a spreadsheet can be set equal in your mind to tables. Within each table is contained a set of rows, and a set of columns.

What are some of the top SQL database / data warehouse platforms options?

For your enlightenment and education, below are some common SQL database and data warehouse platforms.

  • Postgre SQL (Preferred for example use: free and open source, widely used on the internet, multi-OS)
  • Amazon Redshift data warehouse
  • MariaSQL
  • Microsoft Access
  • Microsoft SQL Server (MS SQL Server Express)
  • MySQL
  • Oracle Database
  • SQLite


In addition to straight database programs and data warehouses, there a range of other programs that utilize the SQL programming language for core functions. Below is a short (and rather incomplete list) of other popular SQL applications and uses.

Other Applications of SQL

  • Looker
  • MemSQL
  • Periscope Data
  • Hive (On top of Hadoop)
  • Google BigQuery
  • Facebook Presto


A Bit More About SQL

SQL stands for Structured Query Language. It can be applied in a wide range of manners, including PostGreSQL that will be used in these examples. Further, SQL is the programming language that will be used to communicate with databases in this experience.

To start, a sample SQL statement:

SELECT customer_id, first_name, last_name

FROM sales

ORDER BY first_name



Here’s a quick overview of what I learned, and have consequently shared.

  • What’s a database?
  • How is a database different from a spreadsheet?
  • Why should a database be used?
  • What are some database / data warehouse platforms that operate with SQL?

If you’re just arriving at this article, here’s my running list of articles that detail how to learn SQL.

Upcoming Educational Material on SQL

  • PostgreSQL Installation
  • Databases and Tables Basics
  • SQL Syntax and Statement Fundamentals
  • GROUP BY Clause


  • Advanced SQL
  • Additional SQL Commands


  • Create Databases and Tables through SQL
  • Views
  • PostgreSQL with Python
Exploring marketing career paths by climbing a mountain in Colorado

4 Simple Marketing Career Paths Your Professor Never Told You About

Several months ago, I sat in a warm conference room in the University of Houston Bauer business school. The wind gusted outside;  professors and a couple of brave students shuffled papers on a conference table between presentations. I was privileged to be an advisory board member and mentor at this Enactus UH event.

Unexpectedly (to me), an adjacent student leaned over and asked about marketing career paths. What an intelligent question! I realized determining a marketing career path can be utterly confusing as a student. There are slick advertising agencies, PR boutiques, massive corporations with large silos and vague job titles all around. What on earth is an account executive and what makes it different from an account planner, account manager or anything else?

In that moment, it was my pleasure to share with this student how to evaluate marketing career paths. Some years ago, I was strangely fortunate that by providence I’ve enjoyed such an easy, clear path so far in my young career. Reflecting on that exchange, there are likely thousands of students seeking clarity and guidance on marketing careers.

Below is a simple method that shows you marketing careers at a glance, with detailed explanations below.



In marketing, you make major two choices that determine your career path: where you work and what you do. You’ll either work at an agency or a client and you’ll either focus on branding or direct response. Obviously, there’s room for a lot of creativity and nuance – but a large portion of marketing careers fit this framework.

Where You Work: Agency

We’ll start here, because I’m most familiar with this area. An agency is a 3rd party that a brands such as Adidas or GM hires to help with marketing. Agencies exist because they provide expertise and impartiality that brands can’t get in-house.

Marketing and advertising agencies are a great starting point to master tactical execution. You’ll often be on the sharp end of the spear: pulling reports, writing copy and auditing campaigns. It’s often a fast-paced environment. The offices have bright lights, open concept floor plans, and quirky perks.

Working in an agency is fun! However, it’s imperative you do some homework before joining an agency. I’ve been very fortunate to work at agencies that offer great benefits and pay. My agency experiences have been nothing short of phenomenal. Regrettably, not all marketing agencies are that way. Some agencies  can be volatile if clients leave or have long/tough hours in uncertain conditions. That said, it’s your privilege of choice!

Where You Work: Client

If you’re not the agency, you’re likely the client. If you’re on the “client side”, you’re likely working in-house at a brand like Hilton or Neiman Marcus.

Client side marketing can vary a lot, depending on the marketing maturity of your organization. In some organizations, you may be managing agencies, vendors and strategy. In less-developed or smaller companies, marketing may be closer to sales support.

In general, client-side jobs are more stable and evenly paced than agencies. Deadlines are usually more relaxed and the pay is generally higher compared to agencies. However, marketing can be vulnerable in a corporate setting. If your organization falls on hard financial times, accounting and marketing are the first functions to be cut.

Much like agencies, there are great brands and tough situations. Do your homework!

What You Do: Branding

Now you know where you can work in marketing and advertising. The aspiring marketer’s next major decision is what you do.

In marketing, you either focus on consumer actions or consumer perceptions. The art and science of branding focuses on consumer perceptions. Branding is a fascinating discipline. You constantly fight battles in the minds of brands and consumers. You must appear first, as the best.

Branding jobs often have “creative” or “strategist” somewhere in the title; a keen sense of strategy is key to your success. To learn more about branding, you should read the classic, “Positioning” by Al Ries and Jack Trout. A caveat to branding-centric positions: you may lack experience in tactical marketing execution at the expense of creative pursuits. If you’re a strategy maven (which is rare), you can survive without concrete tactical knowledge. If you’re weak in strategy, it can be tough to advance your career in this field.

What You Do: Direct Response

The other major marketing avenue is direct response. Instead of focusing on consumer perceptions (branding), you work with consumer actions. Direct response is self-evident, you work to produce an action from a consumer. If you envision a purchase funnel, direct response typically handles the end: making a sale, strengthening a relationship.

Direct response jobs often have “analyst”, “planner” or “specialist” in the title. Working in direct response is fantastic to build practical, tactical experience that can be used in many places & many ways. You’ll find skills such as auditing, research and optimization highly marketable.

The upside of starting in direct response is that marketing is inherently self-promotional: the barriers to entry are low. However, if you don’t chase strategy skills, you can be quickly stuck as a tactician and encounter long-term difficulty advancing your career.

Finding Your Path

The good news: marketing career paths are an open playing field! The bad news: marketing career paths are an open playing field. Hopefully this post brings some definition to a broad field, while pointing out benefits and risks.

DSC_0034 Zach Doty Cover Photo How to Learn SEO in Five Minutes

How to Explain SEO in 5 Minutes

Today, you’re going to learn how to explain SEO to anyone in five minutes! Is it a comprehensive, end-all, be-all example? No. Will it help someone quickly understand the basics of a complex practice? Yes. Let’s jump in. This is, after all, a five minute guide!

Starting Point: SEO is not a black box.

For context, I often hear that SEO is a “black box” and it’s anyone’s guess as to how you rank in search engines. I’m always happy to hear that! It means we have a chance to explain what SEO is really about. Google isn’t a black box. Rather, its algorithms and search engines are so complex at a large scale, it’s difficult to comprehend on a daily basis.
With introductions out of the way, here’s how you do it:
A Job Application
Consider SEO like a job application. You have a resume, references, you deal with a recruiter and a hiring manager. And you want a great career!
In SEO, you have a website, backlinks, the search engine and the user. You want to be found and loved!

Your Resume
Your resume is your website. You control the content and tailor the experience to each opportunity. You balance who you are and what you do.
Your website balances your brand story and products or services. You target keywords to pages of your site, just like your jobs are targeted to certain functions and skill sets.
Which resume would you choose to interview for a Marketing Director?

A. “I’m Leroy, I’m awesome. I’m really cool, I enjoy long walks on the beach and like Ethiopian food.”

B. “Kevin is a seasoned marketing professional who has managed and implemented effective marketing promgrams.”

By the same token, which website would you do business with? One with “high quality products and synergistic solutions”? Or a site that speaks in plain, compelling English?
Your References
Your references are your backlinks, or 3rd party websites linking to your own. You can influence these endorsements and relationships, but not necessarily control them. On both sides of this comparison, quality trumps quantity.

Which of the following references holds the most weight for a candidate?

A. “Little Michael is my favorite nephew, he eats a lot at Thanksgiving, you should hire him.”

B. “Jake paid me some money to recommend him. I guess he’s cool.”

C. “Ryan took our marketing department to the next level with smart strategy. He works well with the team implementing our campaigns.”

Ryan is the best choice. A bunch of low quality or fake recommendations will do a job seeker little good if not harm. By the same token, it’s better to have a few excellent backlinks than a bunch of spammy or fake endorsements.
The ultimate goal
When you’re a job seeker, interviews are great. But you really want the career! Likewise, it’s great to rank well in the search engines, but you want new, loyal customers that convert on your website.

Above all else, optimize your website for your users. The search engine results will follow.

Where to next?

That’s how to explain and understand SEO in five minutes! Obviously, there’s much, much more to learn. However, this will get you on the right path. Dive deeper into SEO with a fantastic Beginner’s Guide from Moz.
DSC_0265 Zach Doty Cover Photo How to Win SEO Long Term

Winning Long Term SEO for Years

A few years ago, the average CMO tenure was 23 months. Yikes. That’s barely long enough to get acquainted and jamming with your staff. Happily, a recent indicates a CMO’s average tenure now sits at 45 months. It’s no secret that personnel and vendors come and go with the executive. For agencies and in-house digital marketers, burgeoning attention and spend in digital means unprecedented opportunity. Naturally, there is tremendous potential for fruitful, long term, agency-marketer-executive relationships. Yet success seems anything but simple, we can’t just ride off into the sunset. (Darn, I like Westerns.) Long term digital marketing engagements still seem precarious at best, especially for Search Engine Optimization (SEO). The “quick wins” and short-sighted quarterly business environment is still firmly entrenched. With a bit of work and love, long-term client-marketer-executive relationships can be profitable foundations that bolster your agency or brand for the next 10 years.

Succinctly, winning SEO for years is a bit like a strong friendship. It’s not perfect, but an active exchange of trust and vulnerability makes something great. It’s not always “up and to the right”. Every friendship is different, but there are guiding principles and helpful tidbits all can apply.

1. Be a Good Wingman: No Paid Links, period. Just don’t do it. More profound material that follows, but an astounding number of folks still buy crappy links. The alleged 3 month benefit isn’t worth your 5 or 10+ year relationship. Consider the latency of SEO: bad backlinks bought today probably won’t help much this quarter. However, they could be indexed in 1-2+ years and derail your campaign at a crucial moment. Because you’re a star marketer, you may find yourself explaining this to other. Less enlightened (don’t tell them that!) colleagues, staff and supervisors need to know that optimizing for the user, not the search engine, brings the win home. Provide an enchanting user experience, and results will follow. Bonus: If you want to scope out your link situation, check out Link Detox or use a great SEO software platform to audit your link profile quality.

2. Be a master of reporting and storytelling. A common agency story runs like this, stop me if you’ve heard this one before: 3 months into an engagement, the client loves the work, everyone is excited! 6 months: communication tapers off and so does the work. At 7-8 months, an email arrives, “Can we get an audit of our billings and work?” Next month, “We’re not seeing the value…can we talk?”

Learning to communicate and report intelligently will help you avoid the account/campaign death spin and 9at least) double the life of your engagement. How you say and show success is the lifeblood of your agency’s (or brand’s marketing) future. In agencies, you’ll often hear, “We don’t have time to educate the client.” True, but you surely can’t afford to leave them in the dark. Build small bits of education into your reporting at each step. Your client (or executive) should be educated enough that they could dispose of you, but so satisfied that they’ll never want to.

Reporting over a long time horizon is tricky. Before you have a full year of data, seasonality can make your work look bad if you’re uninformed on market trends. (What if your 6 month evaluation is in a demand trough?) Furthermore, it’s not realistic to primarily report on the same metric month after month. (E.g, keyword rankings) The client or executive may deem organic traffic the determining KPI at your campaign start. However, fascination is fleeting. Revenue or return on investment will likely be your KPI in 12 months’ time.

Use a consistent mix of metrics to paint a rich picture of your phenomenal digital marketing campaign. When you forecast, it’s common to use upper and lower bounds (like economists and weathermen!) to ensure you don’t look like too big of an idiot in any case. Similarly, use “upside metrics” such as revenue generated from organic and ROAS/ROI and “downside metrics” like cost per acquisition and results decay analysis if your client or executive stopped working with you. Assuming sound communication, your reporting should become easier over time. When showing CMO’s and presidents year-over-year, 3, 5 year trends of their performance, we don’t have to do much selling.

3. Learn to live through redesigns. The shelf life of a website is (and should be, to a degree) these days. Blanket statements are a great way to get in trouble. However, many sites (looking at you, Fortune 500 companies) are on the cusp of major changes for mobile friendliness. If you’re around for more than a couple of years, you will see the client’s site go through a redesign. Ideally, you will start the redesign process small pieces at a time. When you present conversion improvement data, mash up clickstream analytics with heatmapping data for compelling improvements.

However, if you’re not regularly testing, you should start. If you approach a redesign without aforementioned experience, here are a few things to keep in mind.

  • You must exercise discretion and attention to detail. Choose carefully which battles to fight. Web design & development projects are notorious for being past schedule, over budget and largely dissatisfying on the whole. Don’t be the unnecessary logo critic and save your clout for things that matter to SEO.
  • Here’s what you do need in a redesign: a seat at the table, the power to veto content, technical matters and the ability to test after completion. Conventional wisdom in design is at best, a starting point. Best practices will not transfer from one client to the next.
  • Here’s what you don’t need: Approval on typography, creative direction of promo tiles and so on. Did we mention you should pick your battles?

A redesign done well can bolster traffic, interest and conversions. A poor redesign can break a site, its rankings and the business behind it. Mind your technical details such as URL aliases, file extensions, redirects, robots files, sitemaps and more. Don’t know what I just rattled off? Send me a message, I’m happy to explain.

4. Visible Progress. Related to reporting, what tangible value can you demonstrate on a regular basis? Clients and executives often refer to digital marketing as “black box” and “murky”. Their perception is understandable. However, many facets of digital marketing are so precise and complex at scale that simple explanations are very difficult in quick meetings. What pieces of content or site changes can you point to? Given that digital is complex, your client or executive must have concrete, simple wins they can shop as their own.

5. Deep involvement in the client’s business. Don’t get left out in the cold. Many agencies suffer volatility because they enter late in the marketing game with a client. Brand managers suffer irrelevance by thinking small, too late. When a client or executive says sales or down, don’t nod and make a cursory note in your moleskin. Unleash a barrage of intelligent questions about their customer intelligence, acquisition, retention and sales process. Your ability to engage on a deep business level (down to P&L and EPS) will be a large determining factor in your long term success.

This is not an all-inclusive guide to winning SEO long term. However, it’s my hope that this will a jump off point for your team as it conquers its next digital marketing success.