Saul Medeiors Affiliate Marketing: The Most Common Demand Generation Mistakes That Sabotage Your Success

Author: Joe Paone

Sabotage is an interesting word. As a verb, it means to deliberately destroy, damage, or obstruct something. As a noun, it refers to the 2014 movie starring Arnold Schwarzenegger about a team of elite DEA agents that are being taken out one by one. Spoiler alert: It turns out it was someone on their team who was doing it.

Sabotage Movie

While sabotage infers that there is intent (usually from an opposing force), there are times when we do it to ourselves mistakenly and become our own worst enemy. When it comes to demand generation, even the most seasoned B2B marketers have fallen into this trap and sabotaged their success without knowing it.

Hopefully, I can help you avoid this disaster by shining a light on the most common pitfalls that demand generation marketers may run into. I’ll cover three big mistakes now, but if you’d like a deep dive on the below and/or you’re interested in learning about additional mistakes, you can register for my upcoming webinar, 8 Biggest Mistakes Demand Generation Marketers Make and How to Avoid Them.

Let’s take a look at three big mistakes that demand generation marketers make and how you can avoid them:

1. Pre-Existing Biases

Whether you have decades of experience in demand gen or are just starting out, we all have pre-existing biases that we may carry with us. For the seasoned marketer, it could come by way of a long history of successes and failures that have shaped your decision-making process. For the newbie, your biases could come from how you perceive marketing should be done based on how you have interacted with marketing in the past. In other words, you’re only considering marketing techniques that have worked on you and those in your immediate circle. When it comes to specific marketing tactics, biases can be very costly if you don’t keep them in check.

It’s important to recognize both your positive and negative biases as you develop your demand generation strategy. For example, you may have a positive bias towards something like paid search and believe that it’s the most effective way to drive demand. At the same time, you may carry a negative bias towards social media and believe that there’s no way to generate demand through that medium. (If you read our Definitive Guide to Social Media Marketing, you’ll learn why this is simply not true.)

The key to removing biases is to rely on data to inform your decisions and be open to testing when no data exists. When you’re leveraging data, it’s important to look not only at the top-of-the-funnel metrics (i.e. cost per click, cost per acquisition, etc.), but also all throughout the funnel. Specifically, you’ll want to tie programs back to later stage metrics like net new opportunities, pipeline created, and revenue generated.

Taking the negative bias of social media as an example, when analyzing your data, you may find that you have a high cost per acquisition on your paid social media campaigns. At first glance, you might think this is confirming your bias that social media is not effective because it seems more expensive than other tactics. However, when you analyze bottom-of-the-funnel metrics, you may find that social media drove the most net new opportunities out of all your other marketing programs. When you compare the total cost of your social media programs over the number of opportunities generated to other programs you are running, you may find that social media actually yields the lowest cost per opportunity of all your programs.

2. Inaccurate or No Attribution Analysis

As a demand generation marketer, you’ll most likely agree that attribution analysis is extremely important. Proper attribution can help you remove bias, as the above example highlighted, but it should also be the primary driver of determining a program’s success. A demand generation marketer should be able to associate revenue generated (or pipeline created) with the marketing program(s) that contributed to that revenue (or pipeline). Conceptually it sounds easy, but it’s often difficult to run accurate full attribution analysis of your programs without the proper tools.

Top-of-the-funnel metrics like cost per click (CPC), cost per acquisition (CPA), and cost per lead (CPL) are important factors as they provide a basic indicator of how successful your programs are and can be leveraged to optimize programs, but they are not the only factors. The problem with only looking at top-of-the-funnel metrics is that they only tell a part of the story. In order to understand the whole story, you must be able to track all the interactions your prospects and customers have with your marketing programs. This includes looking at middle-of-the-funnel and bottom-of-the-funnel metrics as well.

Ultimately, proper first-touch and multi-touch attribution analysis will give you a more holistic view of how your programs are performing. When you tie back bottom-of-the-funnel metrics to top-of-the-funnel costs, you are able to more accurately optimize your programs based on impact to the business. First-touch will show you which programs or channels are best at bringing the right type of people into the funnel and multi-touch will show you which programs or channels are best at pushing those people through the funnel.

3. Not Segmenting Your Database

It still surprises me how many marketers don’t use segmentation considering that the only way to get the right message to the right person is to properly segment your audience. Many companies bypass this by emailing a generic message to their entire database hoping that it will resonate with enough people to make it worthwhile. Other companies attempt a form of segmentation by uploading individual lists to their email service provider (ESP) for one-off sends. Outside of just email sends, the power of segmentation becomes clear when you consider that it extends to other channels—allowing an organization to show different content on their website to different people, serve different digital ads to different people, etc.

Segmentation starts with three few basic components:

Demographic: Specific information related to that person (e.g. age, income, gender, and job title)
Firmographic: Information related to that person’s company or industry (e.g. company size and annual revenue)
Behavioral: Includes all the trackable behavior (such as pages visited on your website, emails opened, content downloaded, etc.) a person has performed.

With those building blocks, you’re able to more accurately determine what type of message, content, and product or service is most likely to resonate with a specific segment. You can then leverage those segmentations to deliver the appropriate message to the appropriate people at scale. However, keep in mind that segmentation relies on accurate data (which I’ll cover in more detail during the webinar).

This is just the beginning—join me for my upcoming webinar, 8 Biggest Mistakes Demand Generation Marketers Make and How to Avoid Them, on October 14^th at 10am PT, where I’ll cover these same mistakes in more detail and expose five other common mistakes demand generation marketers make that sabotage their success.

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