The Market Authority Index could not exist without AI.
It was not an existing consulting service that we later decided to automate. It was designed and built around capabilities that AI made possible. Ironically enough we may not have designed it if AI had not come along as it generated a new need.
The Market Authority Index assesses how convincingly a business demonstrates its authority within a particular market. It examines evidence across areas such as customer impact, market position, expertise, reputation, commercial substance and the structural clarity of the brand’s digital presence.
Doing this properly requires more than reviewing a company website.
A typical assessment involves researching the business, examining independent evidence, identifying relevant competitors, understanding the surrounding market and applying a consistent methodology (The MAI Standard) across every brand.
It is a substantial research and analysis exercise. Without AI, completing it at meaningful scale would be prohibitively slow and expensive.
The traditional approach to market research often forces a choice between depth and scale.
You can study a small number of companies in detail, or collect relatively shallow information about a much larger group. Doing both is difficult because every additional business adds hours of research, verification, comparison and analysis.
AI changes all that.
AI allows us to examine more evidence, follow more research paths and compare more businesses while maintaining a consistent analytical structure.
The Market Authority Index methodology, assessment criteria and scoring standards remain human-designed. AI supports the research and analytical process, while the methodology determines what evidence matters and how it should be interpreted.
That distinction is important.
The value does not come from asking an AI model for its opinion of a brand. It comes from combining a defined methodology, structured evidence, appropriate controls and human judgement with the research capacity of AI.
Having a methodology and access to capable AI models was only the beginning.
We still needed an operating environment that could co-ordinate the entire assessment process reliably.
Our earlier implementations included building the full workflow inside a dedicated automation environment. This gave us considerable control, but it also introduced complexity.
Individual stages had to be connected and maintained. Information had to pass reliably between research, scoring, document generation and data storage. Changes to the methodology could require changes across several parts of the workflow.
The system worked, but operating it required a significant amount of technical attention.
This highlighted an important lesson: the capability of the underlying AI model is only one part of an effective AI system.
The orchestration layer matters too.
For a complex assessment to be repeatable, the system must understand the process, use the right tools, preserve context, verify its work and produce consistent outputs. It must also be easy enough to adapt as the methodology develops.
Strawberry has become our agent platform of choice for the Market Authority Index because it makes operations considerably easier.
Instead of treating every stage as a separate technical integration, we can give an AI agent a defined skill, a methodology and access to the appropriate research and business tools.
The agent can then manage the workflow across research, analysis, scoring, data management and report production.
For us, the three most important improvements have been simplicity, reliability and visibility.
The process is easier to operate. It is easier to see what has been completed and what remains outstanding.
Most importantly, Strawberry works within the way the Market Authority Index is actually produced. It supports a multi-stage research and judgement process rather than forcing that process into a rigid series of disconnected automations.
This allows us to focus more of our attention on methodology, evidence quality and the commercial meaning of the findings.
A recent added benefit has been efficiency as Strawberry does what it does.
A full brand assessment previously consumed approximately 350 to 500 AI credits. This is typically €3.50 to €5. The same type of assessment can now typically be completed using fewer than 100 credits.
That is not simply a reduction in operating cost.
It changes the range of work that becomes commercially and practically possible.
We can assess larger groups of businesses and create more representative sector benchmarks. We can investigate specialist markets that might previously have been too narrow to justify the research cost. We can update existing intelligence more frequently and compare patterns across countries, sectors and business models.
We can also spend more time investigating the findings that matter.
Once the basic assessment process becomes more efficient, attention can move from gathering information to answering the more valuable questions:
These are the questions that turn a score into useful market intelligence.
We are now also allowing AI to batch process once we confirm a new sector or subsector and it emails the progress to us as it works.
The value of the Market Authority Index increases as the number of brands included in it grows.
An individual assessment shows how one business performs. A complete sector benchmark shows how that performance compares with the market. Multiple sector benchmarks begin to reveal broader patterns in how authority is created, demonstrated and recognised.
Greater efficiency therefore creates a compounding benefit.
More assessments lead to stronger benchmarks. Stronger benchmarks lead to better conclusions. Better conclusions help businesses understand not only where they stand, but why they occupy that position and what they can learn from the market around them.
This is particularly valuable for small and medium-sized businesses.
Many strong businesses have deep expertise, loyal customers and a meaningful record of delivering results, but much of that authority is poorly documented or difficult to discover. They can be commercially credible while appearing structurally weak to someone encountering the brand online for the first time.
The Market Authority Index is designed to make that gap visible.
As we expand the Market Authority Index, maintaining its independence remains essential.
A business cannot buy, influence or obtain a Market Authority Index score by purchasing services from Digital Scorecard. Strawberry does not determine which companies should score well, and neither does any single AI model.
The score is produced through a defined methodology (MAI Standard) applied to available evidence.
AI enables us to find, organise and analyse that evidence at a scale that would otherwise be impractical. Designed standards determine how the evidence should be assessed.
This combination is the foundation of the system.
It provides the reach and efficiency of AI without abandoning the structure, context and judgement required for credible market analysis.
We are now using this increased efficiency to expand the number and range of markets we can assess.
That includes building larger sector cohorts, producing richer benchmark intelligence and examining how authority differs across industries, countries and business models.
It also creates the potential for more frequent updates. Markets change, evidence grows and a company’s authority position can strengthen or weaken over time. A more efficient assessment system makes it possible to monitor those changes rather than treating market research as a one-off event.
AI made the Market Authority Index possible.
Strawberry is making it easier to operate, more reliable to scale and substantially more efficient to expand.
For us, that opens up a whole new world of possibilities.
If you want to understand how visible your business is to AI-driven discovery, and where your authority actually stands in your market, the Market Authority Index is a good place to start. It measures where you are, so you can see clearly what needs to change.