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Podcast: Marketing Optimization - Leveraging the Right Data & Technology for Your Brand

Insights / 09.21.2018

Red Door

In today’s marketing landscape, marketers rely on data and technology more than ever before. While marketing technology allows us to gather data, it also provides the ability to automate and optimize nearly every phase of the digital marketing lifecycle. Enter marketing optimization – the process by which a brand or organization improves their marketing efforts, and ultimately, maximizes their desired business outcomes. 

In this episode of The Marketing Remix, Justin Gabbert, Director of Marketing Strategy & Optimization, and Kevin Aron, Manager of Paid Search, discuss optimization, its impact on today’s marketing tactics and how it's reshaping marketing strategies as a whole. 
 

At a high level, what do we mean when use the term optimization? 

In marketing, more often than not, we're operating in an environment with constrained resources, in the form of budget, people, etc. What we’re trying to do with optimization is stretch those resources further by making iterative improvements. Optimization is often closely tied to experimentation, and that a lot of times we're experimenting in a statistical and scientific format to understand how we can make an improvement with the resources we have.  

Optimization is also enhancing the overall experience for the people you're addressing. As a digital marketer, you’re closely targeting people and trying to attract those people, so optimizing that experience for them is a big part of the marketing optimization mix.  

Platform best practices is also a significant aspect, whether that be algorithms and organic search, new rules in ads, or new criteria and media. Continued optimization for all these things allow marketers to get the best scores out of the platforms and pay the lowest cost.  

What are some of the other areas that people can be optimizing within the marketing funnel?  

At the top of the funnel, optimization has really been towards the lowest CPM, but this may not be optimal in every case. So, we start talking about audiences and how we reach the right person with a very valuable impression and valuable engagement. Optimization tends to come into play in this space, as we test different messages, test creative, and even get into testing the core identities of a brand.  

As you move your way down the funnel, we have search engine optimization, paid search, and email. There are so many ways to optimize for email specifically, whether it be simple subject line optimizations or email segmentation, looking at what your audience responds well to, what type of messaging they are more drawn to, and what content they want to see.   

For SEO and paid search, we’re going beyond the keyword which has been a staple for so long, and really looking at these audiences and how you can adhere your messaging, your bid prices, and your bid time to where people are in the funnel. Audience segmentation allows you to change your messaging and re-engage people. Once you have those segments, there are multiple tools that allow you to create similar audiences using their artificial intelligence and engage similar people that you may not know how to attract.  

How should brands approach the process of optimization? Where do they start?  

The reason we're all doing this and coming back to the funnel is that we're trying to make the buck stretch further. If you optimize lower in the funnel at a lower cost, you can take those funds and push them back up to the top of the funnel. Ultimately, the main goal is reducing the friction going down the funnel and then pushing that budget back up to the top, so you can reach more people.  

The best place to start is really at the bottom of the funnel to make dollars stretch further. People in this stage are close to converting and may be only considering one other competitor. Next, focusing on the analysis is key because it's hard to build a hypothesis unless you have some sort of insight to drive your hypothesis. From there, you start testing hypotheses. 

Is optimization a linear process or does it vary based on tactic, medium, etc.?  

There are many different ways to look at this. The process is defined in that you need the information, you need to look at the information, and you need to analyze what that information means. However, what that is can vary a lot and one of the key points is being open to testing. Testing keywords can be a very consistent, linear process, but as you start to move into messaging and audiences, it becomes more of a spectrum. 

How is optimization impacting today’s marketing tactics?  

When it comes to optimization, there is a set expectation that failure is okay as long as it's calculated failure and it's quick failure. A lot of companies now are embracing that kind of concept of, "Let's get something into market, and then we can optimize and experiment and improve from there." The mentality is starting to shift that it's okay to test something as long as you're not spending 10% of your budget on tests. At any point with your ad spend portfolio, you want to make sure you have some budget going towards finding those new opportunities and hopefully beating competitors because of that. 

Ultimately, optimization makes us smarter with fast data and fast analysis. You want to test frequently and set barriers that aren't going to lag too long, so you can make good decisions. Rules change frequently, whether it's algorithms and organic, the amount of ads that show up on a search page, or where those ads show up. So, when a change happens, we find a strategy that adjusts for that change.  

How do you keep up with optimizing for algorithm changes? 

To some level, you need to continue to test things that you may have tested in the past. In the context of websites, what works today probably won't work in three months or won't work as effectively. If we're always testing and retesting and getting things back into the flow, then we'll have things that have lost in the past that will end up winning again. So, we have to keep iterating and retesting things that may not have won in the past to make sure we're paying attention to that. 

Where does automation come into play? How can marketers leverage technology to automate some of their marketing processes?

The biggest challenge right now is getting enough different types of variations into the market. You have to have different ad types, you're going to have to have different pieces of creative messaging, but I think that's overhyped a little bit. You really only need to select three variations and test those. We usually prioritize based on the audience, highest value, and channels that are converting at the highest rates. We really start there and then work our way backwards, but it does put a little bit more stress on you, as a marketer, to start thinking more strategically about the consumer experience and creating the assets to change the consumer experience. From there, the algorithms are going to get those pieces in the market and help you optimize towards the best one. 

On the Google side, with automation, they give 14 different headlines and five different descriptions and let the machine match it up based on what it understands from the user and where the user is and the funnel. With automation, you can test a lot quicker without going through so many approval processes. 

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