What is the best digital marketing / marketing framework?

 

How the RACE Framework can help you improve your digital marketing

Marketing frameworks are really useful tools to help us plan, manage and optimize marketing. They’re particularly useful for digital marketing, since it’s so complex today because of all the digital channels available. This is shown by our customer lifecycle visual (below), which suggests the many different touchpoints that potential communications may have with their audiences.

The example shown in this visual is for a B2B scenario where different nurture activities are used to help convert interest in a product or service through to purchase. Many similar stages are involved with B2C marketing.

In this article, I’ll explain how and why we created the Smart Insights RACE Framework for online and multichannel marketing and at the same time, explain some of the key features of marketing frameworks. When I created RACE, it was my view that it would be useful to develop a framework that worked better for digital channels than classic marketing frameworks, but since customers use both physical and digital channels, the framework would work for both.

We will also look at different types of frameworks, with examples and consider some of their strengths and weaknesses.

Types of marketing frameworks

Within both marketing and specifically digital marketing, there are different frameworks that can be applied to different situations.

These are the different types of framework that I have seen most often:

1. Consumer behaviour framework - this describes how users respond to communications and buy, i.e., it’s the steps of a buying process. The first visual in this article is a consumer behaviour framework. The AIDA marketing framework is the best known example of a behavioural framework, sometimes known by academics as a ‘hierarchy of response’ model.
2. Marketing activity planning frameworks. We originally created RACE to help provide a comprehensive breakdown of key activities that to be controlled for effective marketing today. This is useful when you’re looking to perform a digital marketing audit to review your marketing to identify which activities you need to improve. As I’ll explain later, the more detailed breakdown of RACE contains 25 key activities and we define further Standard Operating Procedures (SOPs) to expand on that, so that marketers can prioritize which activities they need to work on as part of marketing planning.
3. Marketing process framework. This defines the stages or steps involved in creating and implementing a strategy and plan. Although RACE is now well-known as a planning framework, it it fact has a process component too - this defines the series of steps that are needed to create the digital marketing plan.  The second part of RACE defined in our in-depth article on the RACE Framework and process describes a process of:

• • Opportunity - Complete audits and set targets based on forecasts
  • Strategy - Prioritize marketing activities to achieve targets
  • Action  - Take action to implement that strategy - we do this as part of 90-day planning

4. Marketing maturity framework - these are useful for comparing how advanced different aspects of marketing such as digital marketing, SEO or social media are within an organization, so they can be used for auditing and benchmarking to identify improvements.See our digital marketing maturity framework for examples of these.

What is needed for an effective marketing or digital planning framework?

There are many classical marketing frameworks available which have been developed ‘over the years’, such as AIDA, described in our article Marketing models that have stood the test of time.  There are also many specific digital marketing frameworks developed since Internet marketing emerged in the mid-1990s (see our post listing digital marketing models).

Since there are so many alternatives, to choose the best framework for you, it’s worth thinking through what you are looking for in a framework. This is how I see the four main requirements:

• Clear purpose  - an effective marketing framework is one that is used to help people looking to understand, audit or manage marketing. Digital marketing is still relatively new, but as we have said, is complex, so we have found that many people are looking to create a digital marketing strategy or plan. That should be the main purpose - to create an effective plan.  This is the case with RACE, but other frameworks such as thee 6Cs are more focused on consumer behaviour
• Realistic model balancing simplicity, complexity and reality - frameworks provide a structure to help simplify a complex situation, so they are a simplified model of the reality.  This is a difficult challenge for the framework creator. If the framework is too simple, it will be easier to understand, but potentially too simple. To get around this challenge, with RACE we created three levels of complexity. There is a simple, 5-part breakdown, but this is divided down further to cover all the digital marketing activities that need to be managed. Each of the 5 parts of RACE is split into 5 more parts, to give a 5X5 = 25-part structure. Each of these 5 is broken down further to define more specific tasks or standard operating procedures (SOPs) that need to be managed. The marketing funnel framework is an interesting example of a model that struggles to balance simplicity with realism. In recent years it has been criticized for not being realistic in portraying complex customer journeys. We explore this in our article by Annmarie Hanlon: 'Customer journey models to master your omnichannel strategy' and discuss in more detail below.
• Application to different businesses and sectors - A framework is most useful if it is open to a range of different sectors. It’s commonplace to develop consumer or retail marketing frameworks, like Google’s ZMOT model, but they aren’t applicable more widely, for example into B2B. We developed RACE so that it can be applied to different business and revenue models - from online-only to multichannel businesses - so it applies to businesses both where transactions occur online, or sales involve human interactions.
• Actionable - This is why we developed RACE, we wanted to create a practical framework that can be used to improve results from marketing. To do this the framework must help complete an audit, review against competitors, create a strategy and then implement and review a plan.

Marketing Funnel Frameworks

Hierarchy of response frameworks, such as AIDA, are often formed into funnel models to assist planning. The RACE Framework is an example of a funnel model. Since these models are linear they have been criticized, since commentators believe they are an oversimplification and don't reflect the non-linear nature of decision-making.

Based on empirical research, in 2009, McKinsey & Company suggested an alternative non-linear customer journey model to the traditional purchase funnel. Their research was founded on interviews with 20,000 businesses in the USA, Germany, and Japan. We describ it further in this article on alternative customer journey models.

More recently, BCG in their 2025 article, It’s Time for Marketers to Move Beyond the Linear Funnel, also asserted that we need to move beyond the linear marketing funnel model to what they call 'influence maps'. This is based on the assertion that if you 'force-fit' touchpoints into the linear model it can miss a lot of nuance about how consumer behaviour and media and marketing planning to influence consumers works in practice. They hinted at this complexity as follows:

As an alternative, they suggest that influence maps can be used which show how different consumer behaviours, that they label 'Stream', 'Scroll', 'Search' and 'Shop',  occur in parallel.

This visualization gives more flexibility in describing different journeys. In the following example, two purchasers of a similar consumer product have completely different research strategies and actions on the journeys.

They suggest that, in the future, the power of AI analysis to analyze data about touchpoints and GenAI to create compelling creative will make it possible to deliver more effective media planning analysis to support the most influential journeys.

Despite this innovation in thinking, I don't believe this means that the linear funnel 'is dead'. Far from it. Its simplicity still has a number of benefits. A funnel-based framework like RACE remains popular since it enables strategists to:

• Audit the maturity and effectiveness of marketing activities with the aim of making them more efficient, i.e., identify gaps in managing channels effectively
• Set objectives to improve engagement across the funnel
• Develop strategies that prioritize activities to improve engagement using channels
• Manage tactical activities to improve always-on activities, e.g., 90-day planning
• Report on performance against these objectives - but including multi-touch attribution (MTA) to assess the contribution from upper funnel activities on conversion

A discussion of this consumer journey model on LinkedIn prompted by Neil Perkin's summary shows that many believe funnels still have their place. For example, Marketing Professor Vincent Balusseau of Audencia Business School said:"

I never quite understood why people (even experts) conflate funnels and journeys. Funnels are not meant to help understand journeys; that's the purpose of Consumer journey maps. Funnels are valuable for various purposes (depending on the type of funnel used, e.g., a conversion funnel in eCommerce, a brand funnel in a brand tracking study, etc.). So, when I read that "Gen Z has broken the marketing funnel," I sigh. The fact that journeys are becoming more complex does not imply that the funnel as a model (and its different variations) has stopped being useful".

What is the best market framework?

To return to the question at the start of this article and by way of a summary, the best framework is one which meets the requirements of being realistic, actionable and applicable to different sectors.  In this article I have focused mainly on planning frameworks, but there are many consumer frameworks too.

https://tinyurl.com/zpt4pd86

The AI-powered marketing funnel: the funnel shrinks to a single prompt

 

What growth marketers can do as AI owns discovery, comparison, and purchase.

Jo McKinney

 

When the journey happens in a sentence

 

Ask ChatGPT a question like “what’s the best running shoe for flat feet under $120” and AI returns a top pick, explains why, checks inventory, and places the order. In 2025, a single prompt can answer, narrow options, and complete payment without opening a browser. The familiar sequence of touchpoints collapses, but at the same time, opportunity expands for brands that focus on content depth, structured data, and instant fulfilment.

Read on for a hands-on roadmap: where to rewrite, what to re-structure, and which metrics help you know if you’re winning when a single prompt can now decide the sale.

 

Awareness – a zero-click reality

 

At the awareness stage, consumers used to find brands via search engines, social media, or ads. Now, generative AI is changing that up. A Bain & Company survey found that 80% of consumers use zero-click AI answers for at least 40% of their searches, meaning they get what they need without visiting a site. That’s led to organic traffic drops in the double digits.

Profound analyzed 30 million AI responses and found ChatGPT cited Wikipedia nearly 50% of the time, while Google AI Overviews leaned on Reddit and YouTube. Perplexity also favored Reddit. Every time a paragraph replaces a link, a visit disappears. WARC reports publishers in Google’s AI Overviews beta lost 18% to 64% of organic clicks. Semrush data on HubSpot’s traffic confirms that by December 2024, blog traffic accounted for just 42% of their organic sessions, down from 77% in January 2024.

 

Still, Google’s May 2025 guidance confirms that valuable, fast-loading, technically sound pages with supporting media continue to surface. When users do click, they stay longer and convert better.

 

 

What to do for awareness: Aim to be the source AI cites in its answer

 

·       Create genuinely helpful top-of-funnel assets that are relevant, comprehensive, and directly answer common user questions:

-        Educational articles

-        Buying guides

-        How-to tutorials

·       Skip tons of keywords and thin content

·       Produce clear, authoritative resources that an AI can lift and summarize (which is what it does)

 

Consideration – from research to recommendation in one chat

 

In the consideration stage, buyers evaluate options (reading reviews, comparing features, seeking recommendations in various forums). Now, users can ask, “Is Brand A or B better for me?” and get a strong answer synthesized from lots of different sources. AI favors pages written like answers, not ads. Pages with schema markup, subheads, and plainspoken language are easier for AIs to extract. If your product pages read like Q&A (What problem does it solve? Who shouldn’t buy it? How does it compare?), the AI can quote you outright.

For brands, this means the traditional mid-funnel touchpoints (comparison pages, customer review platforms, lengthy spec sheets) might get bypassed. A consumer who might have spent an evening reading blog comparisons or watching YouTube reviews could now have their options narrowed down by ChatGPT in seconds. Traffic that used to flow to third-party review sites or your own product comparison pages is diminished. If your product isn’t among AI’s curated picks, you may not even be in the running for consideration.

But being included in AI recommendations builds trust quickly. If a user values sustainability and your skincare brand is eco-friendly, the AI may surface that contextually in its recommendation. This is effectively hyper-personalized, context-aware positioning that would be hard to replicate with a traditionally broad marketing message.

 

What to do for consideration: Hyper-personalized, context-aware positioning

 

·       Make your product data rich and AI-readable.

-        Maintain detailed specs, FAQs, and descriptions (keep them updated)

-        Use clear headers and apply schema markup

·       Leverage public sentiment

-        Encourage strong, authentic reviews

-        Surface review snippets for AI to quote

·       Format product pages as if answering a question (helps people and machines)

-        Comparison tables

-        Real review snippets

-        Problem-solution narratives (I normally hate these but AI likes them)

 

In the messy middle of consideration, depth wins over brand size or clout. Brands offering clear pros and cons, verified reviews, and honest comparisons are cited even when bigger players are not. Yes, fewer users reach your page, but those who do are ready to act because they’ve already done their homework (or their AI has).

 

Conversion – the rise of one-click (or no-click) commerce

 

Perhaps the biggest change is happening at the bottom of the funnel: conversion. AI is not just guiding decisions, it’s beginning to execute them. We are entering the age of conversational commerce, where a customer can go from “I think I’ll buy this” to completing a purchase without ever leaving a chat interface or search results page.

Adobe Analytics reports that generative AI traffic to retail sites grew by over 1200% between mid-2024 and early 2025. Orders initiated through AI chat are converting at significantly higher rates than standard organic sessions.  Fewer steps mean fewer drop-offs. In Shopify’s ChatGPT sales-channel pilot (pilot launched in April), users could say, “Order two more bags of the light roast,” get a confirmation, and complete the purchase, entirely in dialogue. Copilot can build an Instacart cart from a recipe card. The funnel stages blur into one.

This has two major implications. First, web analytics may show fewer checkout visits, not because of lost sales, but because they happen elsewhere. PYMNTS describes this shift as compressing browsing, selection, and checkout into one conversation.

Second, brands may lose visibility into the customer journey. If the AI agent owns the transaction, brands may miss chances to upsell or connect. You may see the order but not know where it came from. That said, smoother checkout raises conversion rates fast. Adobe shows that AI-driven search is rapidly outperforming traditional search in final-stage conversion.

 

What to do for conversion: Ready your e-commerce stack for AI-initiated orders

 

·       Shopify merchants

-        Test the ChatGPT sales-channel beta as soon as it is offered

·       Broaden beyond Shopify

-        Enable chat-commerce in WhatsApp or Facebook Messenger

-        Activate social commerce checkouts on Instagram or TikTok

-        Pilot voice buying through Alexa or Google Assistant

·       Minimize friction, and you’ll see gains.

 

Why fewer clicks can signal a stronger engine

 

By now it’s clear that traffic patterns are shifting. You may experience drops in website visitors at various funnel stages (i.e. fewer people reading your top-of-funnel blog posts, or fewer reading your product pages) and a gut reaction might be to panic. But it’s important to interpret this change properly: some of that traffic wasn’t converting anyway, and some of it is being replaced by better traffic. When discovery, evaluation, and purchase merge into one interaction, there are fewer opportunities for drop-off, and stronger signals of purchase intent. This shift often means less traffic overall, but more meaningful engagement from those who do make it to your site.

 

Building for the agentic era

 

The most effective answer is product-led SEO, or content rooted in genuine user tasks, not keywords. Product-led SEO means creating content that draws in your target customers by solving their problems and integrating your product as part of the solution. It’s a shift from writing generic articles for clicks, to making content that is deeply tied to your product’s value proposition and the user’s needs. Map the real questions, publish complete solutions, structure information so a parser can lift it and surround claims with proof. Google’s own checklist still applies, the difference is that assistants now enforce it ruthlessly.

 

Marketing KPI’s are changing too

 

Measurement must evolve as well. Page views and sessions matter less than three new signals:

1.    Citations inside AI answers

2.    Traffic that originates from those answers and

3.    Sales made without a visible cart page (i.e. ai facilitated checkouts).

Add these to the dashboard or risk misreading performance.

 

Adapt one stage at a time to build a fast funnel

 

When AI guides each step in the consumer journey or marketing funnel, marketing’s job shifts from driving clicks to supplying perfect answers and seamless fulfilment. Brands that master both will own the fastest funnel. Here are a few key takeaways for marketers:

 

·       AI is the new middleman. Prepare for journeys with no traditional clicks.

·       Authority plus depth wins. One great page beats ten shallow ones.

·       Conversational checkout doubles speed. Integrate catalogues with chat-friendly endpoints.

·       Revise dashboards. Add share of AI citations and agent-driven revenue next to classic SEO metrics.

·       Act now. Rewrite one foundational guide so that it deserves an AI citation, turn one comparison page into an answer and activate one chat-based order path. Each small step tightens the link between question and purchase.

 

Getting started with your AI optimized marketing funnel

 

Complete these five moves and you’ll know which answers AI trusts, how answer-style content converts, and how much revenue already flows through AI channels.

 

1. Do an AI visibility audit

Ask ChatGPT, Bing AI, and Google AI the ten beginner and comparison questions you care about. Note which brands they cite and where you’re missing.

 

2. Publish three definitive answers

Fill the gaps from the audit with three deep resources (FAQ + schema + visuals). Aim to become the paragraph an assistant quotes.

 

3. Rewrite one product page into “answer format”

Add a pros/cons table, a competitor column and real review snippets (with Review schema) so the page reads like the response an AI would give.

 

4. Make your store assistant-ready (for ecomm brands)

Conversational commerce is here, and Shopify has begun rolling out its ChatGPT integration. While some users now see in-chat “Buy Now” buttons, most purchases still redirect to the merchant’s Shopify checkout page (this will transition over time). Once available, there’s no setup required. Just make sure your product titles, images, pricing, and reviews are clean and complete in your Shopify backend. For broader reach, enable a WhatsApp Shop by uploading your product catalog through the WhatsApp Business App or API.  With new channels active, your storefront becomes shoppable within conversations.

 

5. Add new KPIs to the dashboard

Track share of AI citations, traffic from AI, and AI-driven sales alongside sessions and conversion rate. Seeing these numbers weekly builds momentum.

 

https://tinyurl.com/2x4mwekj

Need to Accelerate Growth - Start by Overcoming Insanity - and Fixing Your Sales Pipeline

 

Stagewise sales process to analyze sales

BUT WAIT...I've tried a lot of this stuff before - and it didn't work...

I hear this all the time. It is especially true for organizations who have some holes in their Marketing and Business Development strategy and approach.

They have tried a whole bunch of other growth consultants and suppliers previously. They put forth a lot of effort, but got insufficient results.

It's common for companies to try something new - and then expect sales to start flowing in.

But, while sometimes gold can be struck right off the bat, typically it takes more than a tweak to your website, a series of webinars and some new product literature, and attending a few more trade shows.

Overcoming Insanity

The definition of insanity is: "Doing the same thing - and expecting different results."

Most Marketing and Client Acquisition is disconnected - or done piecemeal. The Marketing and Sales Pipeline should:

• Drive consistent leads at the top of your funnel
• Nurture them through the middle of the funnel and then
• Move and connect them to the bottom of the funnel where the sale can happen.

Leads - and thus opportunities - get lost all along the pipeline without the various levels being connected properly with the right hand-off.

Its also important to remember that only a small percentage of leads are ready to buy now - or soon. And as much as 90% of leads can be wasted by not treating them properly.

Unless your sales pipeline has a top to bottom system that covers - and connects - everything from lead generation to sale, pipeline management and growth strategies - you are leaving money on the table. And perhaps a lot more than you imagine...

None of this is rocket science

Good Marketing and New Business Development strategies should not only create bottom line results, but also streamline your efforts to focusing on the things that are the most profitable and most effective - which make them more manageable for you and your Team.

Its definitely worth the effort to identify any holes in your funnel where leads are dropping off - or where money is being spent without a measurable return.

A properly designed and run lead generation machine can make your Marketing and New Business Development efforts:

• More Efficient
• More Measurable
• More Reliable
• More Profitable and
• Result in More Growth

Sounds like something worth doing new.

What do you think?

https://tinyurl.com/35fdvxt3