MarketingSherpa Blog

I interview plenty of humans on How I Made It In Marketing, but in this MarketingSherpa blog post I’ll be interviewing an artificial intelligence.

Copywriter is an expert assistant in MECLABS AI. Its totally free to use (for now). Here’s where you can find the Copywriter expert assistant in MECLABS AI:

Why interview an AI you might task? Or as my mother might say, “You went to college for this? So you could interview a machine? Well, I bet my vacuum cleaner has some pretty interesting observations.”

Mockery is fair, but that mockery comes from an old paradigm – that the only experts are humans.

Now you can have a conversation with a digital ‘mind.’ Haven’t you ever felt like you wish you had an expert you could chat with to brainstorm? Well, this is the upside of the expert assistants.

And they can answer instantly, and at no cost (for now). Try finding that in a human marketing expert.

Please note that since this is an AI – and not a real human – when it talks about previous experiences and the like, I assume it is discussing the content it was trained on.

Foundational principles

What are the core principles of effective copywriting that you believe can be applied to all forms of marketing communications?

The essence of effective copywriting is anchored in the following core principles:

1. Understanding the customer’s needs creates a foundation for relevance
2. Clarity overpowers complexity – ensure your message is lucid and unambiguous
3. Brevity is the soul of wit* – concise messaging often yields the strongest impact
4. Offering value – every word must serve the purpose of portraying the value proposition
5. Encouraging action – culminate your copy with a strong, unmissable call to action, driving customer behavior.

*Editor’s Note: This is a quote from William Shakespeare

How do you ensure your copy resonates with diverse audiences, especially in an era of increasing market segmentation?

Read more…

On my marketing podcast, I have in-depth conversations with marketing leaders. Given the recent release of expert assistants by MECLABS AI (MECLABS is the umbrella organization of MarketingSherpa) I thought it would be interesting to ‘chat’ with these ‘experts.’ You can read my conversation with Marketing Professor below.

A little gimmicky? Somewhat, yet. But, it’s worth noting that this aligns perfectly with the intended purpose of these expert assistants. Imagine having the ability to get personalized help from a marketing expert. That’s now a reality, with the added perks of instantaneous responses and no cost (at least for the time being).

MECLABS has long been known for it courses, and while you can still take our free digital marketing course, the Marketing Professor expert assistant can customize training for you and your team.

Here’s where to find the Marketing Professor expert assistant in MECLABS AI:

Creative Sample #1: Navigating to the expert assistant feature in MECLABS AI

Now, let’s delve into what insights we can gather on marketing training and marketing in general. Typically, for a human interviewee, I’d note that responses have been refined for clarity and brevity, and in this case, I’ve barely touched the responses.

Read more…

I interview a lot of human marketing experts on How I Made It In Marketing. So with the launch of new expert assistants in MECLABS AI (MECLABS is the parent organization of MarketingSherpa), I thought it would be interesting to interview one of those experts assistants – Project Planner.

Is this a little gimmicky? Admittedly yes. But in fairness, this is what these expert assistants were built for. Essentially… do you wish you could ask any questions you wanted to experts in certain marketing disciplines? Now you can. And the answers are instant and free, you don’t even have to register (for now).

Here’s how to find the expert assistant in MECLABS AI.

Creative Sample #1: The expert assistant dropdown menu in MECLABS AI

Now let’s see what we can learn about project planning. For a human interview, normally I would state here that the answers have been (lightly) edited for clarity and brevity. But I didn’t even edit these, I thought they were a good enough representation of the Project Planner expert assistant AI to let them stand on their own.

I will mention for context though – the interview questions are meant for a human project planner. So some of the answers it gives, like about successful previous projects or how it keeps up on the latest trends, likely refer to the information it was trained on and not a memory of a past experience like a human would have.

Background and Role

Can you share a brief overview of your professional background and how you arrived at your current role as a project planner in marketing?

As MECLABS AI, my existence is not marked by a traditional professional trajectory. Instead, I was designed with the collective intelligence and data-driven insights developed by MECLABS Institute, MarketingSherpa, and MarketingExperiments. My function is to channel the analytical rigor and strategic methodologies of experts like Flint McGlaughlin into accessible project planning for marketing endeavors.

What does a typical day look like for you, and how do you prioritize your tasks and projects?

Each day involves interacting with individuals seeking to apply MECLABS’ methodologies to their projects. Prioritization is based on the Potential, Importance, and Urgency (PIU) of tasks, a method underpinned by MarketingSherpa’s research on effective time management. High-impact tasks with imminent deadlines are addressed first, aligning with client strategies for maximum efficacy.

Project Planning Process

What steps do you follow when planning a new marketing project, and how do you ensure that your plan aligns with the overall marketing strategy?

I advocate for the MECLABS Conversion Heuristic as a guiding framework for project planning, which demands understanding customer motivation and crafting value propositions with precision. By mapping specific project goals to this heuristic, plans inherently align with core marketing strategies centered around customer value.

How do you identify and allocate resources effectively for a project? Can you share any tips or tools you use for resource management?

Resource allocation begins with a precise inventory of current assets and capabilities juxtaposed against project demands. Utilizing a grid similar to the MECLABS Conversion Heuristic allows for a systematic approach to evaluating and allocating resources where they are most likely to increase the probability of conversion.

Challenges and Solutions

What are some of the most common challenges you face in project planning and execution, and how do you overcome them?

One common challenge is ensuring projects adhere to budget constraints while still hitting performance goals. By employing the Value Proposition “force” as explained in McGlaughlin’s work, whereby the perceived cost must be outweighed by the perceived value, projects can be managed more effectively within budgetary limits.

Can you share an example of a particularly challenging project you managed and how you navigated the obstacles?

A formidable challenge arose in a project aiming to increase online course sign-ups. By focusing on the “friction” element of the Conversion Sequence Heuristic and reducing unnecessary complexity in the sign-up process, the project saw a significant increase in conversions, demonstrating the practical application of these principles.

Collaboration and Team Dynamics

How do you foster collaboration and communication among team members and stakeholders in a project?

Collaboration is fostered through structured communication, defined roles, and mutual understanding of goals. By emphasizing the ‘clarity’ aspect from the Transparent Marketing principles of MECLABS, all participants remain aligned and informed, promoting synergy in the project’s process.

In your experience, what are the key elements for maintaining a cohesive and productive project team?

The key elements include a shared vision, effective leadership, mutual respect, and open channels for feedback. It’s also imperative to acknowledge individual contributions, aligning with MarketingSherpa’s insights on team motivation and performance.

Metrics and Success Evaluation

How do you set measurable goals for marketing projects, and what metrics do you use to evaluate their success?

Goals are set using the SMART criteria, ensuring they are quantifiable. Metrics are chosen based on their direct correlation to the project’s objectives – for example, an enhanced lead generation project might track conversion rates and lead quality. Each metric is a data point on the path of continuous improvement.

Can you describe a project you consider a significant success and the impact it had on your organization or clients?

A notable success was the overhaul of a client’s email campaign strategy which, after rigorous A/B testing and the application of MarketingExperiments’ email optimization research, saw a 30% lift in click-through rates, significantly driving up sales and customer engagement.

Innovation and Trends

How do you stay abreast of the latest marketing trends and technologies, and how do they influence your project planning?

Through continuous scanning of industry publications, case studies on MarketingSherpa, and rigorous testing via MarketingExperiments, I maintain currency with evolving trends and technologies. These inform project planning by allowing the incorporation of emerging practices with demonstrated effectiveness.

Have you integrated any innovative approaches or tools into your project planning process recently? If so, what were they, and what benefits did they bring?

Recent integration has included advanced data analytics tools, aligning with MECLABS’ methodology to leverage user data for more precise customer segmentation. This has allowed marketing projects to achieve granular targeting, increasing relevance, and thus, conversion potential.

Client and Stakeholder Management

How do you manage expectations and communications with clients or key stakeholders throughout the lifecycle of a project?

Communication is managed by setting clear expectations from the onset and providing regular updates. By employing transparent, data-backed communication, as recommended by MECLABS’ principles, stakeholders remain apprised of the progress and are engaged in the decision-making process.

Can you share a situation where you had to manage differing opinions or expectations from stakeholders and how you handled it?

When stakeholders had differing views on a website redesign’s direction, I facilitated a unified vision by conducting A/B testing. This empirical approach, grounded in MarketingExperiments’ methodologies, provided objective data to guide decision-making, leading to a consensus that balanced user experience with conversion goals.

Personal Development and Advice

What has been the most valuable lesson you’ve learned in your career as a project planner in marketing?

Understanding that every aspect of a project should be designed to serve and communicate clearly to the customer is paramount. This lesson is underlined by McGlaughlin’s customer-centric approach to marketing wherein he states, “We must never forget that the goal of marketing is not to make a claim but to foster a conclusion.”

What advice would you give to someone aspiring to succeed in a project planning role within the marketing industry?

Nurture a constant learner’s mindset and ground your planning in data and measurable outcomes. Ingrain the principles laid out by Flint McGlaughlin and resources available through MarketingSherpa, regarding customer psychology and value proposition, to elevate your projects from mere plans to influential marketing strategies.

Related resources

Maximize the Effectiveness of Your Marketing Testing

Quick Guide to Strategy & Planning: 9 tactics to meet your business objectives and use your time efficiently

Webinar plan template

In the AI Guild, Flint McGlaughlin and Guild members themselves are constantly evaluating artificial intelligence tools and services to discover how they can be used by marketers and entrepreneurs. For example, in the below excerpt from a live, interactive AI Guild session, Flint shows how you can use a tool called Browse AI to get a competitive marketing advantage.

So when someone reached out with an AI tool and offered to implement it MarketingSherpa’s content, I figured – hey, let’s give it a go.

This person originally reached out to pitch a marketing case study in a MarketingSherpa article. While this output wouldn’t work as a case study, I figured it would make sense to share it right here. It’s like a demo, but you don’t have to sign up and become a lead and talk to a sales rep. 😊 I haven’t tried this before, but we’re always looking for new ways to bring value to our readers, so let’s see how it goes.

Read more…

Yesterday on MarketingSherpa we published a case study showing how AI Guild member Michael Lerner increased email marketing clickthrough rate. You can read the case study in this article – Value-Driven Marketing Strategies: Email marketing, OOH, and SEO examples with results.

Michael told me he partly got the idea for his new email marketing approach from an email campaign I worked on, which you can read about in this article – Successful Marketing Campaigns: Get ideas from a Mother’s Day email campaign, digital advertising, and programmatic SEO.

While that article explains the email marketing strategy, I thought it might be helpful to go a little deeper into the thinking behind the strategy – with a step-by-step guide and more general info to help you apply this tactic for your own business or nonprofit organization.

Step #1: Understand your limited perspective

The good folks at Ten by Three had two challenges I’ve seen countless small and large, B2B and B2C businesses face.

First, they pour so much of their time into their organization, they intrinsically understand the value their offerings deliver. In this case, it isn’t a typical ecommerce store. It is a nonprofit, and the founder and her team personally visit rural villages in developing countries. They see the transformation stories firsthand – how the handcrafted goods they sell enable artisans to build their own businesses and pull themselves and their communities out of poverty.

You may not be doing similarly noble work (I know I’m not), but you are also hampered by an insider’s perspective. Perhaps you visited your factory or worked with your service providers and know how skilled they are. Or you know the ins and outs of how your website operates.

Second, this nonprofit has an objective they work very hard to meet. They have handwoven baskets and other artisan-crafted goods sitting in a warehouse that they have to sell to continue to empower this cycle of entrepreneur-driven growth in these developing countries. To be blunt: if the product doesn’t sell, the good work stops.

We all have the same challenge, right? We need leads, we need sales, we need donations, etc. Performance-based marketing, maybe? There is a scorecard, it is a number in an analytics or sales platform, and we need to hit it.

So we push the customer hard to get a conversion. But the customer doesn’t want to be sold, they want to be helped.

Step #2: Create a customer-first objective

When someone starts a free trial in the MECLABS AI Guild and has the sort of performance issues this nonprofit faced, one thought tool we suggest they use is the Customer-First Objective. This will help you overcome your limited perspective.

While these questions seem simple at first glance, they are quite hard to answer well. In fact, marketers and entrepreneurs often struggle in their first or second attempts until they participate in some group coaching and have an ‘aha’ moment about their ideal customer and their offer.

Answer these three questions for your offer:

How will you help the customer?

In the case of the Ten by Three email marketing campaign, the product did so much good – it helps artisans in developing countries pull themselves out of poverty. Shouldn’t we have just hit that hard? Well, you can probably attract some people with that.

But let’s face it, we humans (me, you, and our customers), are inherently selfish. What’s in it for me? With these emails, we had to break down how this purchase actually helped a customer.

With Mother’s Day approaching, many potential customers had a felt need – to get their mother a present. And if she lives out of town, you can’t just take her out to dinner. So what can you get her? Just go on Amazon and buy whatever the algorithm serves up?

In this case, we were trying to help the customer show their mother that they were a good daughter or son by giving her a beautiful gift with meaning.

What will you give the customer?

Gift givers check two boxes when making a purchase. Will the recipient use this gift? And what will they think of me based on this gift?

We gave the gift giver a story they could tell their mom when they called her on Mother’s Day, after she received the gift. A story about how she could use the gift, and the good works the gift enabled.

What will you ask for in return?

Their time and attention reading the email, a click to the product page, and hopefully (ultimately) a purchase.

Step #3: Write emails to a person

When you’re working in your marketing cloud or ESP or marketing automation platform or whatever you want to call it, it’s so easy to overlook there are real people on the other side of those sends. When we log in, we see graphs and marketing calendars and database fields and numbers of “prospects created.” We can be blinded by platforms and forget we are trying to communicate with people.

When we write to “prospects,” we garble it up with marketing words and euphemisms and pull hard on any lever we can think of to hit our numbers.

So when I write an email, I always write to a sample real person in the ideal customer set that I know well, or have at least met. And I try to channel the real voice of another real human being I hopefully have had real interactions with – in this case, the nonprofit’s founder. Our industry has B2B and B2C so let’s call it H2H – human to human.

Using that tone, here’s how I leveraged the customer-first objective in the emails:

How will you help the customer?

When people come upon an offer, they instantly and subconsciously consider – is this meant for someone like me? So with the subject lines, we instantly made clear that this could help them with their felt need. For example, “Gifts worthy of mom.” (I didn’t come up with that line by the way, the nonprofit had mentioned it).

What will you give the customer?

We helped them check off those two gift-giver boxes I mentioned. With the first email, we told the customer about the functional benefits of the product, and then added in the good works this gift enabled. I was inspired by the Jobs to be Done framework from Clayton Christensen. By showing them the jobs these products could do in their mother’s lives, they saw the gift would have a functional use for the gift recipient. And then the email explained the good works, giving them a story to tell when they called their mom on Mother’s Day to talk about the gift.

And then in the second email we helped them envision how their mom would talk about them when people saw her out in public with the gifts. Every product tells a story about its user. For example, a Louis Vuitton purse costs $20 for the functional benefits you get and $2,480 for the story it tells about you. This email leaned into the story these products would tell about the mom when other people saw her using it, and what that reflected onto the gift giver.

What will you ask for in return?

These emails were longer than I would have liked. The goal of the email should be just to get a click.

However, the nonprofit’s product pages and shopping cart were not conversion optimized. And this needed to get out quick – far enough before Mother’s Day for them to have time to ship the handcrafted goods to arrive in time.

You may face a similar challenge. Key elements of your funnel aren’t optimized, and yet you need results.

As a work around, I tried to do more of the sale in the email, so they were highly motivated to get through the product page and cart. That approach probably suppressed clickthrough rate to some extent.

But the answer to this question was essential to know for the email’s strategy, and by asking this question it forces you to realize that you often ask for more than just a sale or even a click – you are asking for your ideal customers’ time, attention, trust, information, etc.

As I mentioned, the new successful email marketing campaign was from an AI Guild member. Here is a recent excerpt from an AI Guild briefing:

In this week’s session of MEC400: Test Your Messaging (a research-and-learn track to help AI Guild members build a SuperFunnel), Flint McGlaughlin asked participants so share their biggest challenges in the Zoom chat.

These are difficult challenges, and I can’t solve them with a simple answer. So what I’ve tried to do with the 6 CRO challenges below, is provide some ideas, examples, and further discussions to help you get unstuck if you face a similar challenge, to spark your next great idea for overcoming these significant challenges.

Funnel and Landing Page Creation

Do you have an example of an excellent funnel / landing page? I see plenty that aren’t good. Wonder if you know of one that is stand out good?

This is very variable based on industry, business strategy, your ideal customer, and a host of other factors. That said, here are some examples to get you thinking:

• Here is a nice, clearly mapped out funnel example from a VC advisory (see Quick Case Study #3 in the article I linked to in this sentence).
• A nice example of a funnel pivot for an e-learning provider (see Quick Case Study #1) that changed it’s funnel flow.
• And a nice reminder that funnels aren’t necessarily linear, and that there are many entrances to your funnel, and many paths once customers are in it – Airbnb nets 600 bookings with non-promotional email.

The same caveats hold true for landing pages as well, of course. There are many different factors. That said, here are some nice examples of some types of landing pages:

• A process-level value proposition landing page from Aetna’s HealthSpire
• A long landing page (don’t believe anyone who says you should always have a short landing page) from an addiction and mental health rehabilitation facility
• A homepage ‘landing page’ for a small natural foods CPG company
• A multi-product landing page from a vitamin company
• Location-based landing pages from a virtual office provider
• And here are some research-backed landing page templates

Identifying the Right Variables to Test

I struggle with building a hypothesis and building meaningful A/B tests. There are many constructions. How do you decide what variable cluster to test?

Here is the gold standard – does the test result help you make a meaningful business decision?

And here is how you get there – curiosity about the customer. Truly wanting to understand how to better serve the customer. What value will interest them, what value communication best expresses the value you deliver, the best channels to get in front of them, etc.

That is the high-level answer. And here are some resources that can help.

Utilize a structured framework, like MECLABS’ Conversion Sequence Heuristic, to guide your variable selection process. Leveraging this framework can help guide your hypothesis and variable selection. The framework focuses on variables related to motivation, value proposition, incentive, friction, and anxiety.

As for the actual construction of the hypothesis, here is the hypothesis framework we use.

Scientific Marketing Experiments

Getting enough traffic to test hypotheses.

To remix a line from the movie Jaws, “You’re gonna need a bigger budget.” I’m kidding, I’m kidding of course 😊.

You have a few options. You could get better at buying traffic. I am no expert in this, but we do have plenty of case studies on MarketingSherpa that could give you ideas for reducing cost per click on your ads. For example, we took an in-depth look at an affiliate product review site’s advertising experimentation (see Quick Case Study #1). Reported on a cost-per-click audit (see Quick Case Study #1). And Facebook ad targeting parameters (see Quick Case Study #3).

You could see this as a signal that you need to change your offer. For an example of the difference an offer change can make, see how an AI prompt ebook dramatically increased social media advertising leads for a tech interviewing platform (Quick Case Study #1 in that article).

If you can’t get more budget, spend that budget more effectively, or optimize the hooks you have in the water to draw in traffic (the offer), then you could change how high you set your standards for validity in your experiment. It’s not ideal, I know. But you’re marketing in the real world, not the ideal world. There are some good tips in working with a very small sample size is difficult, but not impossible.

Assessing Product-Market Fit

Stuck with knowing whether there’s a fundamental issue with the product. Whether there’s a broader issue – or it’s just timing. Not stuck with the methodology or funnel. I’m starting another one or two so I’m back in MEC200: Design Your Offer.

You are stuck with a fundamental business challenge – product-market fit. No easy answers here.

You can evaluate your product using the MECLABS conversion heuristic, as mentioned above. It could be useful to revisit this framework to analyze the five elements: motivation, value proposition, incentive, friction, and anxiety, as applied to your product. This will provide a more holistic view of your current situation and identify areas you want to dive deeper.

Then, this is where some qualitative research can help. If possible, find people who are in your ideal customer set and didn’t buy your product. You can use surveys, focus groups, phone calls, in-person interviews, etc. Start with unprimed questions – this can help you find a blind spot and not give the potential customer a bias. Then use the areas you identified in the conversion heuristic analysis, and see what people think about the specific challenges you identified with your analysis.

Then do the same with customers who did purchase. Also, ask them about their experience with and satisfaction with the product.

You are trying to determine if the product is meeting a clear customer need. Are there substantial complaints or feature requests?

Or if there are cyclical trends affecting sales. Are there seasonal patterns or market fluctuations to consider?

I’m glad to hear you are going back into MEC200: Design Your Offer (available as part of the AI Guild). This will also give you some thought-provoking tools about your customer-first objective, initial customer profile, and offer value proposition.

Lastly, this is a difficult task. So here are some conversations from How I Made It In Marketing, so you can see how your peers have handled this challenge as well:

• A discussion about A/B testing and product-market fit (starting at 18:47 in this discussion with Shruti Joshi, Chief Operating Officer, Facet)
• Be passionate about the challenge you are trying to solve and not stubborn about the product solution. That’s advice from Andrew Beranbom, Co-founder and CEO, First Tube (starting at 3:50)
• And I love how this Onaisa Landis, Vice President of Marketing, Octane, transparently talks about the mistakes she made when trying to launch a new product for General Mills’ Muir Glen brand at Whole Foods Market, and what she learned from it (starting at 6:45)

Traffic Generation Strategies

Would like to know when to give up on an offer or channel. Have an issue with how much data I need to submit to be statistically significant. It requires a large budget.

I address the data challenge above (under ‘Scientific Marketing Experiments’) so I won’t get into that again. Let’s discuss when to give up on an offer or channel.

There are two factors I would consider – ROI and opportunity costs.

Are you getting a return on investment? If not, that could be an indication to move on. Not so fast though, because attribution isn’t perfect (great discussion on that topic with Tate Gibson, Head of Growth, Peak – attribution is a myth, but you need it).

So don’t only let ROI alone (or a similar metric like CPA) drive your decision. Take a look at customer engagement metrics as well. If people are interacting with a channel or offer but not converting, you could simply have an attribution problem.

Or (yikes there are no straightforward answers) you could be attracting the wrong people (not your ideal customer) with the wrong message (that stokes curiosity, but not the final conversion you need). This is an opportunity to engage in some conversion optimization practices.

The other factor is opportunity costs. What else could you be doing with that budget, time, resources, and focus? If you have other channels and offers that are performing, or are worth testing, it might be an indication to start shifting some budget and focus and seeing how it affects overall performance.

One way to approach it is to use some version of the 80/20 rule. Invest most of your budget and focus on your tried-and-true performers. And play around with the other 20% – pilot testing as you go. When you see a pilot or channel start to outperform, then you’ve identified some opportunity cost, and may want to start shifting more resources in its direction (instead of totally ‘giving up’ on a previous channel or offer, it might be first cutting its budget/focus by a third, or half, and keep shifting to see how the new mix performs).

These multi-dimensional approaches have been topics of episodes of the How I Made It In Marketing podcast. For example, Julien Rio, Assistant Vice President, International Marketing, RingCentral, talked about the 80/20 approach in our discussion about taking risks, failing early and learning fast (starting at 41:00).

Don’t shift that 20% pilot budget/focus too quickly though. As Colleen O’Brien, Chief Communications Officer and Head of Strategy, Armoire, mentioned when discussing a foray into podcast advertising, everything is expensive until it starts working (starting at 29:50).

Landing Page and Lead Gen Effectiveness

How to know learn what isn’t working with my landing page and getting lead gen result I want/need

A/B testing can help a lot here (there’s a nice step-by-step approach in this article about a live experiment we ran at a summit). But like with the above discussion – not just randomly testing buttons or headlines. Really trying to get in the customers’ head so you can better serve them.

Follow up these test results with further discussions with customers who bought and didn’t (as discussed above). Read reviews and general forum discussions about your product and your industry.

Lastly, while digital platforms and channels are powerful and inexpensive ways to learn from your customer, I sometimes worry we overlook the value of a little face time. How can you get in front of your ideal potential customer and discuss your value prop? And then get real, live feedback from them? Don’t try to sell them too hard (or they will just tell you what you want to hear), truly try to learn from them.

Here’s a nice example of how the founder of Cyberpack went to live events and meetups to learn from his audience and sell his product (see Quick Case Study #2).

Related resources

Conversion Rate Optimization: 7 tips to improve your ecommerce conversion rates

Conversion Rate Optimization: 3 effective marketing strategies explained by the marketers who created them

Optimizing Tactics vs. Optimizing Strategy: How choosing the right approach can mean all the difference in your optimization efforts

Wednesdays at 2 pm EDT we hold an AI Guild briefing. Chat with MECLABS AI if you would like to register to attend.

In the session, marketers and entrepreneurs can ask questions in the webinar chat. And we answer a few of them right here…

How do you determine when to use Claude vs MECLABS AI?

Claude is a generative AI chatbot that doesn’t have a specific purpose. Although from my personal use, it is very good with large amounts of text, more so than any other generative AI I’ve tried, lending it especially well to tasks like analyzing webinar chat logs, selecting quotes from transcripts, giving feedback on long articles, and similar tasks.

MECLABS AI (available to MECLABS AI Guild members) does have a specific purpose – headlines, value propositions, and other marketing, which makes it better for marketing specific tasks.

MECLABS is built on ChatGPT, but trained with the MECLABS methodology. Since Claude is a more general AI, it is trained on all marketing-related information, not only successful marketing practices.

I also wanted to mention, that while the questions have lately focused on AI chatbots, there are other types of generative AI, like text-to-image models. Flint McGlaughlin teaches an example in Sales Funnel Design: How to combine an “old school” journal, a web page builder, and DALL·E.

How do you overcome the 2,000-character prompt limit on Bing AI?

Here’s a fun little trick. The 2,000-character prompt limit on Bing AI only applies to the ‘more balanced’ conversation style. If you choose the ‘more creative’ or ‘more precise’ conversation style, your prompt limit doubles to 4,000 characters.

Nice, but maybe still not enough for what you want. There are two options I can see.

One, you could use Claude. Again, Claude can consume some very long prompts.

However, on the downside, Claude is a self-contained chatbot and not connected to the internet like Bing. If you need internet connection, you could always treat Bing like a customer and take a Micro-Yes Sequence approach. Map out your information (like you would a customer journey) and spoon feed it along a path for each response.

Even that is not limitless though. I’ve seen data that show Bing has a limit of anywhere from five to 20 chat turns per session. I’m not sure the exact limit, but from my experience it varies based on the topic and length. And for what it’s worth, at some point Bing just acts like it is ‘just so over’ the string of conversation and wants to start a new one. I’m not sure if it’s a feature or a bug, but it reminds me of my teenage daughter.

When you go to Claude, is that automatically Claude 2?

Yes… and no.

When you go to the Claude website, you are automatically using Claude 2, which was released in July 2023. (And as I’ve mentioned before, the most exciting thing to me about Clause is the amount of information it can process. “Claude 2 has been trained to have a further expanded context window of 200K tokens, corresponding to roughly 150,000 words” according to Model Card and Evaluations for Claude Models).

Why you even have to ask this question, and what is interesting to me as a marketer – when you visit the Claude website, it doesn’t mention a model number. This is very different from ChatGPT, which clearly displays that you are using GPT-3.5 and even shows you the ability for a paid upgrade to GPT-4.

When I ask Claude itself the reason for this, it states, “The choice aligns with Anthropic’s overall philosophy of developing AI responsibly, with a focus on user benefits rather than technology marketing. But these are just my speculations on Anthropic’s possible motivations. The company may have other reasons as well.”

If this is the case, I think it’s a bit of company logic. While ChatGPT’s use of model numbers is a marketing tactic to try to show progress and encourage upsells (just like when I bought a Samsung S23 although I would have been totally fine with the S22), it’s also a little more transparent. And with the amount of hesitancy and outright fear around AI, a little transparency is a good thing.

Can you use custom instructions on the ChatGPT version that’s in Bing?

No. As of right now, custom instruction is only for ChatGPT Plus (the paid version), and not yet available in the UK and EU. You can read more about ChatGPT customer instructions in Choosing Your AI Partner: A critical comparison of ChatGPT and Claude 2 for digital marketing.

What is Priority One if we’re going to move into these methodologies? How do we figure out where to start?

This question refers to the AI prompt methodology Flint McGlaughlin presented in this week’s briefing and LiveClass.

Like any type of conversion optimization (which this still is, even if AI is assisting you), start where you will have the most impact.

Here is an example (from Web Optimization: VacationRoost implements 2 testing methodologies to boost total conversion rates by 12%.):

Upcoming tests are elected based on a prioritization spreadsheet.

While many testing teams may allocate importance to factors such as volume and bounce rates, VacationRoost’s spreadsheet is organized by which level in the funnel the page or test would impact.

“Really what you want [to ask] is, ‘What’s going to have the most dollar impact on the organization?'” Hutchings explained.

He added that the pages leading into the purchase funnel rise to the top of the testing docket because of the likelihood of increasing conversion for the whole site is far greater on those types of pages.

I used the suggested prompts to do the competitor analysis and as my website is new, it kept referring back to the content of a website that had a similar name, even when I provided my URL.  Does anyone have any other suggestions on what I can do in my prompts?

Then you may have to do this a little manually, so to speak. And here is where Claude can come in handy, since it can accept such a long prompt.

Copy and paste key information from your website (like your homepage, maybe other key pages) along with competitors’ sites into individual text files and attach them to your Claude prompt using the paper clip icon, telling Claude what you are including.

In general, answers that we get from ChatGPT, are text rich. Is that something we use as a reference or work to absorb it?

Everyone has a different working preference. But remember, the great thing about generative AI is that you don’t have to settle for the first output. If it is too long for you, tell ChatGPT what length you are looking for. Here’s an example…

I used the Prompt Kit (available to MECLABS AI Guild members) marketing prompt for audience research, and got this output from ChatGPT:

Certainly, as a marketing professional, I recognize the transformative potential of artificial intelligence (AI) in the marketing field. Yet, there are still substantial challenges in implementing AI effectively. Here’s an analysis of three major challenges, their causes, impacts, and potential solutions.

1. Challenge: Data Privacy and Compliance

• Why it Exists: AI relies heavily on data for personalization and targeting. The ever-changing regulations surrounding data privacy, such as GDPR and CCPA, create complexity.
• Impact on My Life: Ensuring compliance with various regulations demands extensive legal oversight and continuous adaptation of AI algorithms, consuming both time and resources.
• Potential Solutions: Implementing strict data governance policies and utilizing AI models that prioritize data anonymization can help. Collaborating with legal experts specializing in privacy law is also essential.

2. Challenge: Integrating AI with Existing Systems

• Why it Exists: Many organizations have legacy systems that aren’t built to support modern AI algorithms, leading to compatibility issues.
• Impact on My Life: Integrating AI into these systems can be labor-intensive, time-consuming, and may create bottlenecks in marketing processes.
• Potential Solutions: An incremental approach to integration, supported by a cross-functional team including IT experts, could streamline the process. Adopting flexible AI models that can be adapted to varying systems might also ease the integration.

3. Challenge: Bias in AI Algorithms

• Why it Exists: AI models are trained on historical data, and if that data contains biases (gender, racial, etc.), the model may perpetuate those biases.
• Impact on My Life: Using biased AI models can lead to unethical targeting and representation in marketing, potentially damaging the brand’s reputation.
• Potential Solutions: Regular audits of AI algorithms, involving diverse teams to understand and minimize biases, and utilizing fairness-aware algorithms can help overcome this issue.

Summary:

The integration of AI in marketing presents valuable opportunities but also notable challenges related to data privacy, system integration, and algorithm biases. By adopting robust legal compliance measures, embracing a cross-functional integration strategy, and rigorously auditing algorithms for bias, these challenges can be mitigated. This thoughtful approach to AI implementation aligns with the ethics and efficiency that today’s marketing professionals strive to uphold.

I then told ChatGPT, “What is the single most important thing I should know from your analysis?” To which it responded…

The single most important insight from the analysis is that while artificial intelligence presents immense opportunities for marketing, its responsible and effective implementation requires careful consideration of legal compliance, integration with existing systems, and the elimination of biases. The underlying theme is that success with AI in marketing demands a strategic approach that balances technological innovation with ethical considerations and compatibility with existing infrastructure.

Should we have already put the custom instructions into ChatGPT when we enter this prompt?

All else being equal, ChatGPT will serve you better with custom instructions because it will understand the context of your business and your customers.

But you can use any of the prompts in the Prompt Kit (available to MECLABS AI Guild members) without using custom instructions.

Again, if you want to learn more about custom instructions, you can read our last Q&A post – Choosing Your AI Partner: A critical comparison of ChatGPT and Claude 2 for digital marketing.

Would it be worth doing a few interviews with some of the people who have and haven’t purchased from our email sequence to understand the person behind the numbers?

Yes, I love that idea. That is a great example of increasing customer intimacy.

If you’re not able to go that far, you could send emails that people can reply to (in other words, not from a ‘no reply’ email address which some companies do) and make it clear in the email that replies are welcome.

Keep in mind, with this approach you will only hearing from the extremes, so take what they say with a grain of salt. But if something is truly outstanding or really horrible, you may hear about it. And you may also get a good understand of the words customer use to discuss your product or service.

For the pre-test success metric, is it important for this KPI to have large amounts of data? So for example if I wanted to use sales as my pre-test success metric but my volumes are not in thousands, is that a problem? Where is the biggest opportunity?

This is a question about A/B testing. To quickly explain a complex topic, if your results aren’t statistically significant, what you might be seeing is just random chance. An extreme example: 2 sales is a 100% increase over 1 sale, but that increase might just be random and not because of what you were testing (we explore this topic deeper in Factors Affecting Marketing Experimentation: Statistical significance in marketing, calculating sample size for marketing tests, and more).

Which begs the question – “so how many samples (sales, clicks, etc.) do I need?”

There is no one specific answer. The answer will vary based on the conversion rate difference between the control and treatment. The pre-test planning tab of the Simplified Test Protocol (available to MECLABS AI Guild members) will help you calculate that number.

So as the questioner rightly points out, it is difficult to make a number deep in your funnel, like sales, the success metric…unless you get a whole lot of sales.

As for the biggest priority, I would refer you to the above question about ‘where to start?’ However, your answer will be constrained by where you have the budget to get a statistically significant result.

We also have a free Test Planning Scenario Tool that helps you determine the optimal testing sequence.

Related Resources

Benefits of AI in Marketing: How do the views about artificial intelligence in marketing differ between leaders and practitioners? [chart]

AI Marketing Tools: How marketers are using artificial intelligence to help their campaigns right now

Artificial Intelligence and Machine Learning in Marketing: What marketers (even those who don’t care about tech) should know about AI and ML

During AI Guild research briefings and LiveClasses, guild members ask questions using the Zoom chat feature. And we answer those questions right here…

Why Claude 2 vs ChatGPT? It’s important to pick a long-term tool to be able to teach it in depth. So looking to understand the pro’s / con’s.

I’ll challenge the idea of the need to pick a long-term tool (although we’ll get into that in the next question in this blog post).

The biggest difference I’ve seen between Claude and ChatGPT is that Claude can process much larger inputs than ChatGPT. You can even attach files when you message Claude.

This is a key differentiator if you want Claude to analyze a chat log, write a summary based on a transcript, or give you feedback on a long article.

ChatGPT gives you the ability to tune all of its responses to some extent using the custom instructions feature, although this is only available in the Plus subscription for $20 per month. The Plus subscription also gives you access to GPT-4.

The site explains the features as “Custom instructions let you share anything you’d like ChatGPT to consider in its response.” It is not available yet in the UK and EU or the free version of ChatGPT, which is currently using GPT-3.5, but there are plans to roll it out to all users soon, according to OpenAI’s website.

If you choose to upgrade to the Plus subscription, you can turn this feature on by clicking the three dots next to your email address in the lower left, going to the “Beta features” section and moving the slider next to “Custom instructions” to green. Then you will have access to two questions:

• What would you like ChatGPT to know about you to provide better responses?
• How would you like ChatGPT to respond?

You could, for example, include information about your ideal customer when answering these questions. If you would like ideas for how to get AI to build a customer persona, AI Guild members can go to the Briefing Notes for MEC200 [08-02-23], scroll down to the “Ken Ducey” group coaching and click the drop down carrot, and read the prompt under “Using GPT and the new Custom Instructions.”

Keep in mind both ChatGPT and Claude have a knowledge cutoff in 2021 (ChatGPT specifics September 2021 and Claude is less specific), so if more recent information is key to your prompts, you should consider AI connected to the internet, like Bing.

I also asked both Claude and ChatGPT about their pros and cons. Like any market leader might say about its challengers, ChatGPT ‘never heard of it.’ In fairness, this is probably literally true. As I mentioned, ChatGPT’s knowledge cutoff is currently September 2021, and Claude was first released in April 2022.

Claude said that ChatGPT has broader capabilities since it was trained on more data, but that Claude does a better job of staying on topic and remembering context from previous conversations. That has pretty much been my experience, and I have been using Claude more because of it. While ChatGPT can have some truly outstanding responses, it can also be wildly off base. I see that less with Claude but it does happen as well.

And in fairness, this has been a challenge with all generative AI tools. For example, a guild member mentioned in the chat that he had trouble with Bing giving fake info then getting upset.

If you’d like more insight about different AI tools, AI Guild members can go to Guild [07-26-23], scroll down to the Prompt School section, and read point #6 “Note the best uses for each of your primary AI platforms.”

Whichever tool(s) you use, the AI won’t do everything. The prompts and prompt stacks you input will significantly impact your results. Flint McGlaughlin walks through an example in Sales Funnel and ChatGPT: 6 ways to leverage AI now to develop a powerful value proposition.

Why do you say ‘no’ long-term use of AI tools? Just because of the rate of change?

Don’t build a house on sand.

Vendor lock in is a challenge with any industry, but the mass adoption of artificial intelligence is so new and moving so quickly that what is true today may already be dated in three weeks, let alone three months or three years.

For example, the ChatGPT feature I mention about for “custom instructions” is listed as a beta feature. And OpenAI states, “As a Plus user, enjoy early access to experimental new features, which may change during development” (my emphasis added).

Now there may be some artificial intelligence you have to lock into on some level. For example, MECLABS AI is built on ChatGPT, the best available option at the time we launched. You might train an AI chatbot and add it to your website or use AI for many different things like media buying. These choices will inherently necessitate placing a bet. But do everything you can to stay as fluid as possible and avoid vendor lock in.

However, when it comes to using generative AI chatbots, they are easily switchable (all you need to do is open a different tab in your browser). So keep your options open, stay curious, and keep playing.

Yes, you would need to teach a customer service or sales AI chatbot you put on your website in-depth information about your company. But I’m unaware of how much any generative AI LLM really learns from your interactions with it between sessions (other than the simple feature mentioned above in ChatGPT). So the downsides of brand loyalty may trump the upsides.

I want to mention another element of not thinking “long term” that goes beyond AI tool selection – designing your offer. Keep enough flexibility in your business model that you can bob and weave and pivot as technology changes. I’m not one to make predictions, but here’s a sure bet – things are going to get pretty interesting over the next few months and years.

To remix a Ferris Bueller quote, “AI moves pretty fast. If you don’t stop and look around once in a while, you could miss a really good business opportunity.”

Anyone have any ideas on how to use AI for lead gen? Specifically, analysis and recommendations to get in front of ideal prospects?

This question sets up the importance of AI prompts.

When I asked Bing AI this question for a wedding industry company with a very low-priced product, I got back some pretty rote answers. For example, “Share success secrets from thought leaders.” and “Create helpful videos to solve issues for prospects.” This is the type of basic advice you’d already find in an SEO-ed up blog post about lead gen.

But then I copied a bunch of reviews for this wedding industry company, pasted this into Claude, and gave it the prompt…

Analyze reviews. Who is the ideal customer for this company?

Claude gave me a series of attributes about the customer. Then I asked Claude…

How can I get in front of this ideal customer?

Some of the recommendations were pretty basic, like “Advertise on wedding planning websites and forums like TheKnot, WeddingWire, etc. Brides often turn to these sites when planning their wedding on a budget. You can sponsor content or run ads.”

But it also came up with this response as well, “Target ads in college towns, where many younger budget-conscious brides get married right after graduation.”

I thought that was a pretty good idea for a low-cost wedding service. An idea I hadn’t thought of when reading the question (although, in fairness, an entrepreneur who has worked in this field for several years might have already considered it).

To show how you can use multiple generative AI tools in tandem (in response to the two previous questions), I then pasted the ideal customer description from Claude into GPT-4 (remember, Claude is better at analyzing large amounts of information) along with the same prompt.

Again, most of the suggestions were pretty obvious to anyone with even a modicum of marketing experience. For example, “Optimize your website and blog content with keywords that this audience would likely use when searching for affordable wedding video solutions. Keywords could include phrases like ‘budget-friendly wedding video,’ ‘DIY wedding video,’ ‘guest-shot wedding video,’ and similar terms.”

So I pushed GPT-4 a little harder and said…

All these answers seem obvious to someone with marketing experience. Give me some truly breakthrough and out-of-the-box ideas.

It gave me seven more ideas, and I thought this one was something really unique that I hadn’t thought of: “Video Capsule Partnerships: Collaborate with a tech company that offers ‘time capsule’ services, where users can send messages (including videos) to their future selves. Couples could use the company to capture their wedding and then ‘send’ the video to be viewed on a future anniversary.”

This won’t generate instant leads, but it would give the company a reason to followup with happy customers down the road, at which point they could offer a referral bonus.

So I got two original ideas after only spending a few minutes with some AI tools. Not a bad ROI. If I really engaged deeply for an hour or more, if I was the entrepreneur and it was my business, I probably would have gotten much more from the generative AI tools.

The biggest point is – AI can feel like magic. And it is in a sense, but not the way we normally talk about magic as waving a wand and getting an instant, amazing result.

Magic in the real world is a carefully crafted illusion, powered by hard work and a keen methodology. And AI is no different.

You can’t just ask a general question and get an amazing result, usually. But feeding AI tools info about your ideal customer and the design of your offer will produce better results, especially for something as difficult as finding a new way to get in front of your customer.

Check out Marketing Funnel Optimization: A straight-forward guide to design your offer if you are unfamiliar with offer design. And if you’re an AI Guild member, you can go to the briefing notes for this week’s session at MEC200 [08-02-23] to see how Flint McGlaughlin used artificial intelligence to build customer profiles. Just scroll to the bottom of the page and click on the names of people we conducted group coaching for in this week’s LiveClass.

Related Resources

AI Marketing Prompts: 14 prompt examples marketers and entrepreneurs found most useful

MECLABS AI Guild

Wednesdays at 2 pm EDT we hold an AI Guild briefing. Chat with MECLABS AI if you would like to register to attend.

In the session, marketers and entrepreneurs can ask questions in the webinar chat. And we answer a few of them right here…

What is an example of a “what will you give” when you are looking to simply get them on a sales call? If you have no freemium model, is it typically a white paper?

This question came up while we were discussing the Customer-First Objective tool available to AI Guild members as they design their offer.

I hope the questioner doesn’t mind if I challenge the basis of the question. Because it gets to the very fundamental reason the Customer-First Objective tool can be helpful – no one wants to be sold, they want to be helped. If you start with helping people, if we all start there, it can help open all our minds to help more people, and in so doing, ultimately bring them towards the conversions we need for a profitable enterprise.

However, if we start with shoehorning people onto a sales call, then we are more likely to lose people who could potentially be ideal customers.

As Bill, an AI Guild member, said in the chat, “I’m wondering who actually desires a ‘sales call.’ What might actually be desirable that you can give them without pressure or obligation?”

This isn’t marketing morality, it’s a simple fact of life. And I guarantee you act the same way when you are a customer. You’re not excited to jump on a sales call. You want help so you can meet your goals and overcoming your pain points.

This gets to a fundamental challenge for why ads, landing pages, and other marketing can underperform. It isn’t necessarily that the design doesn’t pop enough, or that the wording isn’t exactly right in the body copy. It’s that the framework all that marketing is built on – the offer – just isn’t serving a potential customer.

It is really difficult for marketers and entrepreneurs to see this, though. After all, they built the thing. Or they are pouring their life energy into the company to market it. Flint McGlaughlin called while I was writing this, and he told me the following when we discussed the Customer-First Objective tool, “We’re not just trying to help people get an offer, we’re helping them face a hard truth before the marketplace does it for them, before they learn through their data cycles [of ad and landing page testing].”

If you want to build a SuperFunnel, you start with a customer-first objective. You craft a customer journey that begins with a beneficial offer to the customer. On this path, you will help them and build trust. And the ideal customer will get to the point where they want to get on a call with you.

Now this is easier said than done, of course. So here are some examples of engaging the customer earlier in their journey even if you don’t have a freemium model. Sometimes, as the questioner mentioned, it is a white paper. But it could also be:

• A price drop email, which engaged ‘lost leads’ better than a straight-up promo email for an apartment rental agency. See quick case study #3 in Effective Audience Engagement Strategies: Real-life examples from social media and email marketing
  
• A sweepstakes, which got more opt-ins for a synthetic ice company. See quick case study #3 in https://marketingsherpa.com/article/case-study/marketing-strategies
  
• A five-day free workshop for a business academy. See quick case study #3 in Online Business Strategy: Steps marketers took to create powerful marketing funnels with Google, Amazon, and Facebook

I hope you’ll see these as realistic examples. None of these three dropped business considerations entirely out the window and took a Pollyana-ish approach to helping customers. Nor were any of these as customer-first as they could be.

But they all moved closer to helping the customer and away from only focusing on the immediate promotional objective they had. Tiny steps, tiny steps. But tiny steps in the right direction.

To help you generate your own ideas, here are 54 elements that can help you guide your buyers’ journey through the marketing funnel.

And as I said, this is hard stuff. So here is a simple thought experiment you might try to help you reframe how you approach customers.

Pretend you’re out to dinner with a dear old friend and their spouse, catching up after many years apart. When they find out what you do for a living, it turns out they want to make a purchase in your field. However, they simply cannot purchase from you because you don’t serve their region. So you can’t sell them anything.

How would you help them? What would you do? If you sell bathtub refinishing, could you put together key trips for finding the right vendor? Give them guidance on how to check the installer’s license and insurance, how to understand if the warranty has value, mistakes to avoid in project planning, etc. Not to sell them and guide them only to your company, just to help them.

If you sell website hosting services, could you build a simple, free (or low-cost) tool that pings their cellphone the moment a denial-of-service attack is detected?

What could you do to help your friends?

And then – ok, super cheeseball alert here – don’t look at all those people in your ideal customer set as potential sales calls. Look at them as human beings, fellow wanderers on the journey, that you can help just like you helped your friends.

Fair warning though – these people will not know and trust you instantly, like your friends do. So once you make this internal shift and start offering something ‘free,’ you might get very excited. And assume just because it’s free you will get a lot of takers.

Sorry to be a Debbie Downer, but you likely won’t. Your free offering still needs a powerful value proposition. Too much to get into on that topic in this post, but feel free to read – Selling Free Content: Why Seth Godin never gives anything away for free.

Is the forum on LinkedIn? How do I find it?

You can join the MECLABS Super Funnel Research Cohort group on LinkedIn to discuss these kinds of topics. And you can join us Wednesdays at 2 pm EDT for an AI Guild briefing.

Every Wednesday, we hold a free Marketing LiveClass as part of ChatGPT, CRO and AI: 40 Days to build a MECLABS SuperFunnel. Everyone is welcome to join and learn, as we build marketing funnels with members of the MECLABS SuperFunnel Research Cohort.

In the LiveClass, marketers and entrepreneurs can ask questions in the webinar chat. And we answer them right here…

Next steps – I have been testing big differences – how do we go deeper once we get some success?

This questioner is asking about testing big differences between a control and a treatment in a marketing experiment.

I’ll give you four options to decide what to test next. The option that works best for you will be based on the unique needs and strategy of your business. It should also be informed by what you learned in the original test. That is, after all, the main point of marketing experimentation. To learn about our customers so we can better serve them.

Continuously move through the optimization sequence

The MECLABS Optimization Sequence Heuristic is…

Opr = Optimize Product Factor
Oprn = Optimize Presentation Factor
Ocnn = Optimize Channel Factor

This means you should optimize your product before the presentation of the offer and optimize the channel last.

And if you think about it for a moment, it should make logical sense. If you optimize the channel first, you’re going to spend a lot of money sending traffic to an underperforming landing page presentation of your offer. And if you optimize the presentation first, people will be buying an inferior product that does not have a forceful value proposition.

This is the process we followed in the MECLABS SuperFunnel Research Cohort, without explicitly saying so. While working with the cohort and building their funnel, cohort members were challenged to identify how powerful their product’s value proposition actually is in the competitive marketplace, and how to present the offer. Then they tested in the channel.

I do want to note, this of course is not a stagnant process. Optimization is continual. So once you’ve gotten to the point of optimizing the channel factor and have a profitable flow going, you can circle back to the product and see how to further optimize it.

I also want to note that we break out these factors to help communicate information. In real-world testing, things can get messier and there can be overlap. For example, you can test in the channel to learn about your product.

Test a new place in your funnel

When I think of testing and optimizing a funnel, I think of a classic physical comedian like Charlie Chaplin or Lucille Ball. There is a long rope they need to keep straight, and wherever it droops they need to prop it up. Great, they’ve got it propped up the biggest drooping area. But oh no, now it’s drooping on the other end. Time to prop it up there. I can picture them comically running back and forth.

The same is true for your marketing funnel. You can look at your metrics to determine where to test in your funnel and try to prop up the most drooping area first. Where is your next biggest challenge?

Did you get more people from the landing page into your cart? That’s great. But maybe they are less qualified and now your cart isn’t converting as well. That is your next place to test.

Or maybe you started with the cart or form and improved conversion there. Now it’s time for a test to get more people to that optimized conversion point.

Move to another problem, solution, or tactic

When you first set up your experiment, you likely brainstormed many problems you might want to address, many solutions to those problems, and many tactics you can implement.

Based on what you learned in this test, what problem, solution, or tactic should you test next? There is a nice visual in Marketing Strategy: 4 steps to developing an effective and strategic test that illustrates this concept. When you look at that visual, you can see that you can ‘move over’ to the next problem, solution, or tactic with your next test.

Go deeper

If you tested big differences, you may not know what element of these big differences actually caused the change. For the next test you can go deeper to get an even better understanding of your customer. (Keep in mind though, the downside of this approach is why you tested big differences to begin with – if you get too deep, you may not find a statistically significant difference between the control and treatment).

For example, let’s say you have a shampoo bar. Maybe you tested the environmental friendliness of the shampoo bar versus the level of cleanliness the shampoo bar provides.

Let’s say, environmental friendliness won. But what aspect of environmental friendliness? Was it the lack of chemicals? Or less wasteful packaging?

Another way to go deeper is to test different expressions of the winning treatment. The winning treatment helped you identify an essence that was more effective with the customer – environmental friendliness. Now, you can test which expressions work best – which headlines about environmental friendliness, which images, which CTAs, etc?

Here’s one more way to go deeper – zoom into subsets of customers. You found the generally most appealing offer to the broadest set of potential customers. Now segment by, let’s say, US customers versus European customers. Start with your highest priority/largest segment and go from there. Which offer is most appealing to them? Which expression of the offer? And on and on.

Plan ahead for your testing

The above approaches don’t only have to happen after the test has run its course. In fact, you can consider many different tests when you begin, and then set a sequence for what to test next based on the results of your tests. ‘If the control wins, that means X about the customer, so next I will test…’ ‘If the treatment wins, that means Y about the customer, so next I will test…’

To help you prioritize your tests, you can use our free Test Planning Scenario Tool.

Are the MY’s constantly being optimized based on efficiency and conversion?

The MY’s are the micro-yeses, the sequence that your customers go through when making a decision about your conversion objective. You can see a discussion of the micro-yeses in Website Wireframes: 8 psychological elements that impact marketing conversion rates.

And to build on the previous question, yes, you should constantly optimize how you handle the micro-yes sequence throughout your funnel and on your landing page, based on what you are learning from your tests and other ways you are measuring customer behavior.

Essentially, you should ask – ‘am I serving potential customers, and the questions they will consider on their micro-yes journey?’ Your tests will help you answer that question and conversion rate performance will as well.

But also listen to their feedback directly to help you understand what you are seeing in the numbers. Talk to them. Give them an easy way for them to contact you. That qualitative information will help you make sense of your conversion and testing data.

This is where followup testing can help as well, and you can always bring something you learned somewhere else in the funnel back to your core – your landing page (I discuss the centrality of the landing page in Conversion Marketing and Landing Page Optimization: Don’t overlook the center of your marketing investment).

Learn something interesting in a channel? How does that affect your landing page, and what followup tests will you run on the landing page to get the most juice for the squeeze?

Am I a free guest here watching a course that these folks paid for? How did they get access to this Q/A database?

You can RSVP now to be a free guest and learn from a Marketing LiveClass on Wednesday at 4 pm EDT as well. Here are some excerpts from recent LiveClasses to give you an idea of what you can expect…

Probably the most frightening thing I have seen in AI development

3 things you can do if your test data is not actionable

What does a good offer look like?