The TIPI framework
A structured approach to understanding customer journeys, planning digital experiences and building content
The area of SEO/inbound I’m most passionate about is the intersection between the customer journey, content strategy and information architecture. I’m interested in how you plan and operate large websites that consistently address user and business needs.
IBM is a big company. We have hundreds of products across hardware, software and cloud. We have a large consulting business.
To be able to systematically, and consistently, deliver on the goals of user and business value (which is a big work in progress), we needed to create scalable strategies and methods that worked across IBM’s entire portfolio. Every category we operate in has wrinkles and nuance, but there is also a common backbone shared across them. Our goal as the central platform team was to build infrastructure and programs that support the 70-80% that is common across our portfolio and then provide individual teams with enough flexibility where they can bring additional nuance and specificity.
In order to do this, we needed to identify the common backbone that exists the portfolio. What’s the customer journey, set of page/content types, content programs and IA patterns that can be shared across the portfolio?
In order to answer this question, we developed what we call the TIPI framework.
What is TIPI? Topics, Information Needs, Page Types and Information Architecture
The TIPI framework is a four step approach for building the backbone of digital journeys on the web. It is fundamentally about understanding the contours of your category and customers and then designing strategies and journeys rooted in that nuance.
It starts with understanding the core set of topics (e.g. cloud computing, men's jeans, first person shooters, etc) related to the given product you are ultimately trying to market. When developing the initial topic list, it's important to be as exhaustive as possible, but then begin tiering and prioritizing within that exhaustive set.
With an exhaustive set of topics, you then build a database of the hundreds of related keywords of each set of topics and look for common modifiers for those topics (what is, best, color, fit, reviews, etc). These modifiers tell you what the most common information needs are associated with the topics relevant to your business. This list is also tiered and prioritized.
With an exhaustive set of information needs associated with a topic, you then analyze the types of pages that rank for each query type (category pages, product pages, explainer pages, blogs, review sites, etc). These represent the bare minimum page types that will need to be present on your website in order to rank for the relevant traffic in the category.
Finally, the types of pages that rank help you to understand the intent of a given query (e.g. when someone types in "hybrid cloud" they really want explainer content on hybrid cloud vs. when someone googles "dedicated server" they want to buy). The different types of intents can be used to construct a buyer journey model (like IBM's universal experiences framework) in which different page and query types are clustered together in different journey phases. Information Architecture is how we then specify connections of related pages together on the website into a logical set of journeys.
This approach is not rocket science, it's just a methodical and reliable way of planning that is guaranteed to be aligned to customer needs.
With that summary, let's dive a bit deeper into each of the four areas.
Understanding Topics
Topics are the macro categories of interest related to the product or service we are trying to market. They are things like cloud computing, ai, microservices, etc. They are not individual keywords. Each of these topics will likely have dozens, hundreds or even thousands of mid and long-tail keywords that contain the primary topic (e.g. what is cloud computing, microservices architecture, ai marketing).
The way to think about the relevance of topics to your product or service is not a binary one. It's a sliding scale of relevance.
One way to think about this universe of relevance is the topic bullseye.
The closer a query is to the bullseye, the higher your conversion rate is likely going to be.
Branded queries - people searching the name of your brand, product or service are always going to be your highest quality audience and the one most likely to deliver most of your short-term outcomes. People often have a variety of things they need to understand about your product (pricing, integrations, reviews, etc) before trying and buying, so making sure your product and service experiences are comprehensive and compelling is the best way to deliver better results today.
Exact topic - the next most relevant topic sphere is the closest exact topic to your product or service. If you sell a product that does Robotic Process Automation, then the topic is "Robotic Process Automation." This topic should be very obvious and is the unbranded category the offering is most closely associated with.
Related topics - from the exact topic, we make the universe a little bit bigger and look for related topics. These are the keywords that are typically part of how your primary keyword is defined. For example, in a tool like Clearscope you can clearly see the topics that are most closely related to Robotic Process Automation (business process, workflow, digital transformation, artificial intelligence, etc). After RPA, these are the most important unbranded topics/categories to include in your topic map.
Audience interests - the broadest perspective on topics is simply caring about what your audience cares about. HubSpot builds tools for marketers so they build content for marketers regardless how closely related it is to "CRM for SMB" (which is really what HubSpot specifically does). As an example, they rank on page 1 for "marketing org structure." They don't have a marketing org structure product, but they are absolutely reaching their target audience (marketers, likely leadership) with that content. It may not turn into CRM sales that session, but being consistently useful and relevant to your target audience is a legitimate strategy and how HubSpot built their business and how Digital Ocean (via their community tutorials that primary target general developer content) built theirs.
Understanding Information Needs
Once you have a handle on the topics related to your business and your audience, you can start to build the picture of what people need to know about these topics.
The process for this is pretty simple. Take each of the topics in your topic map, plug them into an SEO tool like ahrefs or BrightEdge and export all the related keywords that contain the original seed topic in the keyword.
For example, you want to export all of this stuff.
You want to export all of these keywords for every one of the topics you identified. Once you have a database you can start analyzing common query patterns across product and topics (and you will likely want to separate the two).
One of the women on my team (Emma Archangel) did great work around this in cloud computing market and the output looked like this.
This data set gives you a sense of total opportunity associated with a modifier and the frequency that the modifier shows up across topics. Things like “what is” and “software” show up in nearly 90% of cases and are obvious candidates for being part of a universal model.
Each individual topic will also have specific queries, but the common set can be the foundation of repeatable programs within your business and repeatable patterns on your website.
Understanding Page Types
With a perspective on all the common query types, we can then start analyzing what types of pages rank for each of these query types.
The simple practice is to just search for the different types of queries and start making notes of what you see in terms of what type of content ranks. One of the keys of this exercise is understanding intent. When someone types in a certain type of query, what do they mean by that? If they google "restaurants" do they want explainer content on what a restaurant is? Do they want a guide to open their own restaurant? Or are they simple looking for restaurants close to them?
You don't need to know the answer to this question just by looking at the query. All you need to know is that Google knows. And if you do the query, look at the results and synthesize what you see, then you will know too.
From those notes, your job is to produce recommendations on different types of pages that need to be on the site in order to rank for the types of queries that buyers and users in our category often search for.
And once you have the page types you need, you then get down to specifying the components for each of those page types. The options and arrangement of these components then become the templates in your CMS.
Example Solution Template
This approach is a useful starting point for determining what types of pages you need on your website and what content needs to be on those pages.
You can add other pages types into your site as you see fit/necessary, but starting with this set can give you a set of confidence that you are delivering what will be most important to your users, and by extension, what will be most important to search engines.
It’s related to both this section and the next, but recently we have become very interested in Object-Oriented UX and are working toward a world where every page is comprised of core content and a collection or related objects from across the site.
Understanding Information Architecture
With our topic and product taxonomy, query types and their corresponding page types, we now have the raw materials of a website. We have the atomic components that need to be composed into something that's a logical journey and experience.
The key to doing this is thinking about journeys from two primary perspectives. First, moving forward in the context of a subject area (e.g. learn about machine learning generally and then exploring what products and services IBM has to offer associated with machine learning) or moving laterally within the context of a journey phase (e.g. learn about machine learning and then learn about a related topic, deep learning).
The reason why we have to plan across both dimensions is because users take both journeys. From our very top of funnel explainer pages, we see about 5-10% of users progress deeper into the site and then nearly 2x as many read more explainer content on related topics. We have hundreds of people every month that visit 10+ explainer pages in our library. We call this “Wikipedia-holing” someone, which should be an immediately familiar behavior to anyone that has ever used Wikipedia.
Some people might contend that this is negative and you want forward motion in the journey, but we don’t agree. If someone isn’t ready to evaluate or buy products, and they are just trying to learn, the best and smartest thing you can do is facilitate that.
The way we start doing this type of IA planning is by creating a model of the buyer journey and aligning our query types and page types to that journey model.
The nice thing about this approach is that if you work the problem in this order, you don’t need to start your buyer journey with a pre-conceived notion of what is ought to be. You can simply look at the data, at the information needs in the categories you serve, and then cluster those needs into common stages and voila you have a buyer journey.
Si Quan Ong over at ahrefs just did a post on the buyer journey that had some similar approaches. And what’s most important is not that your model be exactly right in terms of the labels or clusters (ours are different!), but rather that all the real information needs in your category are actually captured as part of your framework. The buyer journey is just an abstraction of the atomic requirements that sit underneath it.
Conclusion
The most important thing to understand about the TIPI model is understanding what it is and is not. TIPI is primarily a framework for addressing the self-directed buyer journey. It is intended to be a structured approach for reaching buyers that are actively researching categories, products and services.
TIPI provides the strategic foundation for making your business more consistently relevant and discoverable on the web throughout all stages of the buyer journey. It helps you take a methodical, data driven approach to page templates, content strategy and information architecture.
An early version of the TIPI model is how IBM generated $250M of Lifetime Traffic Value (LTTV) in 2021.
TIPI is ultimately about understanding what your customers care about and then designing a digital experience to give them just that. It's about making your company more relevant by being useful to your audience.
And unlike other channels and approaches, it's an approach where value compounds year after year without requiring increases in budget to increase traffic. Every year, as long as you are consistently investing, you should be growing your footprint of evergreen content that delivers values to your customers.
And because it's a method more than an explicit journey model, it's an approach you should be able to apply to any product or service.
I don’t know if you are a rockstar or a serperstar, Bryan, but I miss working with you!