Scott Brown

Good marketing is a great way to kill a bad product. Ultimately, marketing is based on the substance of the product and if you're product isn't delivering value to the right customer, then it can / should fail. Marketing may recommend targeting a different customer group, or find ways to repackage your product value, but ultimately you should also be taking a hard look at your product and make sure it is delivering substance the market wants.

First you need to understand the problem. Rather than thinking about all of the things that are "wrong," start by finding a segment of customers that IS buying your product DESPITE the current situation. This could help you identify value propositions, ICPs, messaging, geographies, etc that are better aligned with your product today that you can build around. Having a clear picture of who is buying today and why will give you a solid foundation to conduct your typical SWOT or other frameworks. Of course, you might decide that the customer that is buying today is NOT who you want to sell to, but that may require changing the product and not just the go-to-market.

Email content creation and automation are critical, but don't forget to use tools to assess the deliverability of all of those fancy emails you just developed. Some marketing automation platforms like HubSpot have some of this functionality built into their "Email Health" scores in the campaign manager, but you should make sure your organization also implements tools like Google's Postmaster Tools (https://www.gmail.com/postmaster/) or a deliverability testing platform like Litmus. Also make sure to regularly clean your email lists with tools like EmailListVerify, NeverBounce, MailFloss to remove invalid address and reduce your bounce rates.

LinkedIn authoring co-pilots like Topial (https://taplio.com/) or AuthoredUp (https://authoredup.com/) can help you optimize and scale up your LinkedIn profile development. In addition to generative AI support, they offer a variety of tools around content repurposing, commenting management, audience identification, etc that save a lot of manual time. Analytics are also centralized, making it easier for you to measure the ROI of your efforts.

One frequently overlooked set of free tools are the ad transparency services from Google, Facebook and LinkedIn. These allow you to view the ad creative any company is running on these sites -- and in some cases, the targeting variables they are using. It's a great way to see what paid demand gen your competitors are running. Google = https://adstransparency.google.com/ LinkedIn = https://www.linkedin.com/ad-library/home Facebook = go to the company's page and look for Ads Transparency under the "About" section

Yes, you should set objectives and measure your outcomes, but in some instances your goal is really to learn something more about your audience or market. In those instances, it's important to develop a series of rational experiments about what you want to learn. Have your team document some hypotheses and then develop incremental tests that only change one variable at a time (for example, changing the ad targeting while keeping the creative and the offer the same). The key is having the team document what they learned at each step and to refine their hypothesis. Teams that I've seen fail at this either try too many experiments at once, or fail to document/measure what they're trying to learn.