How to test your strategy with the market before spending: the complete guide to predictive simulation for business decisions

Predictive simulation is the ability to test hypothetical scenarios with AI models before executing any real action. At Galaxies, Synthetic Personas answer “what if” questions about price, positioning, competition, and strategy in hours, generating evidence before budget is committed.

Every strategic decision is a bet on a future scenario

What is predictive simulation in business?

It is the ability to test hypothetical scenarios with AI before executing any real action. Synthetic Personas answer “what if” questions about price, positioning, channel, and competition in hours, generating data about how the real market is likely to react.

The difference between a good strategic decision and a bad strategic decision is rarely the quality of the executive’s reasoning. It is usually the quality of the information available at the moment of decision.

It is the quality of information. A wrong pricing decision can consume 6 to 24 months of sales cycle before it is corrected. A failed brand repositioning can cost between R$10 million and R$100 million in rebranding, media, and lost market momentum.

The data confirms it: according to CBInsights, 35% of business failures are related to product-market errors, portfolio decisions, and positioning decisions made without sufficient validation.

Predictive simulation is the technology that changes this equation. Instead of executing to learn, you simulate to know, and only then decide what to execute.

The difference between predictive simulation and business intelligence

BI analyzes the past by answering “what happened?” Predictive simulation models the future by answering “what would happen if?” BI uses real historical data. Predictive simulation uses behavioral AI models to generate responses about scenarios that have not happened yet.

BI and predictive simulation do not compete. They complement each other. BI explains what happened to sales. Predictive simulation answers what would happen if you changed the price, message, or channel to correct the problem.

Five concrete scenarios Galaxies answers before execution

Which types of decisions benefit from predictive simulation?

Pricing, positioning, channel, portfolio, and communication decisions. Any situation where the company needs to choose between options with relevant market impact, and where the cost of being wrong is higher than the cost of researching before execution.

Scenario 1: Pricing decision

“If we launch the product at R$199, how does each customer segment react compared with R$299?”

Synthetic Personas from different audience clusters evaluate perceived quality, willingness to pay, and likelihood to purchase at each price range.

Real application: Mahta Bio used this model before launching its first product. With three price ranges tested on Synthetic Personas from the target buyer profile, it identified the price with the highest adoption probability and went live with more confidence.

Scenario 2: Competitive risk

“If a competitor launches a product similar to ours at a 20% lower price, what is the probability of migration by customer cluster?”

The simulation identifies which customer segments are most vulnerable to migration and which attributes need to be reinforced in communication before the scenario happens in the real market.

Scenario 3: Channel decision

“If we move distribution from an indirect channel to a direct channel, who loses and who wins in each region and customer profile?”

The simulation maps the impact by cluster before the company invests in logistics and commercial restructuring.

Scenario 4: Brand repositioning

“If we reposition the brand from premium to accessible, how does perception change among the segments that buy the most today?”

Repositioning is one of marketing’s riskiest decisions. Predictive simulation quantifies that risk by segment before any communication change is made.

Scenario 5: Media budget optimization

“If we cut media budget by 30%, which campaign should we preserve to minimize awareness loss?”

Instead of linear cuts, the simulation identifies which vehicle, format, or message has the highest marginal impact on awareness among priority segments.

Real application: Bradesco Seguros applied a similar model in media planning for a launch and recorded a validation cycle 10.5x faster than the previous process, with 93% savings in cost per respondent.

How to implement predictive simulation in practice

How can predictive simulation be used for strategic decisions?

Six steps: define the decision to be made; map the relevant audience profiles; create or activate representative Synthetic Personas; formulate hypothetical scenarios as clear questions; analyze responses by segment; and use the results to choose what to execute.

1. Define the decision. What choice needs to be made? How valuable is it to know before executing?

2. Map the relevant audiences. Who will be affected by this decision? Which segments matter most?

3. Activate the personas. With available data, personas can be activated in 48 hours.

4. Formulate the scenarios. Turn the strategic alternatives into clear “what if” questions.

5. Analyze responses by segment. Look for differences in acceptance, resistance, and expected behavior.

6. Decide what to execute. Use the evidence to reduce uncertainty before budget is committed.

Predictive simulation versus traditional scenario research

Is predictive simulation different from scenario research with focus groups?

Yes. Scenario research with conjoint analysis costs between R$15,000 and R$60,000 per round and takes 3 to 8 weeks. With predictive simulation using Synthetic Personas, the same insight arrives in hours, with a cost up to 93% lower per respondent.

Traditional scenario research with conjoint analysis is one of the most sophisticated and expensive approaches in market research. It takes weeks, costs tens of thousands of reais, and can test only a limited number of scenarios per round.

With predictive simulation, the same type of insight is available in hours. More scenarios can be tested, more clusters compared, and the company can iterate as many times as needed.

For completely new phenomena with no historical data, exploratory qualitative research still generates hypotheses no synthetic model can anticipate. What changed is scaled validation: now it can be done synthetically, in a fraction of the time and cost.

Frequently asked questions

What is predictive simulation in business?

It is the ability to test hypothetical scenarios with AI before executing any real action. Synthetic Personas that represent the target audience answer “what if” questions about price, positioning, channel, and competition in hours, generating data that guides strategic decisions with information instead of intuition.

What is the difference between predictive simulation and business intelligence?

BI analyzes the past, answering “what happened?” Predictive simulation models the future, answering “what would happen if?” BI uses real historical data. Predictive simulation uses behavioral AI models to generate responses about scenarios that have not yet occurred.

Does predictive simulation replace traditional market research?

For decisions that need to test hypothetical scenarios quickly, yes, predictive simulation can replace part of traditional research. For completely new phenomena without historical data, the approaches complement each other: qualitative research generates hypotheses, predictive simulation tests those hypotheses at scale.

How much does predictive simulation cost compared with a scenario focus group?

Scenario research with focus groups or conjoint analysis can cost between R$15,000 and R$60,000 per round and take 3 to 8 weeks. With predictive simulation using Galaxies Synthetic Personas, cost per respondent can be up to 93% lower and delivery can happen within 48 hours.

Does predictive simulation work for product decisions, not only marketing?

Yes. The most common use cases on the Galaxies platform involve pricing, competitive risk, distribution channels, brand repositioning, and budget optimization, covering CMOs, CPOs, CFOs, and CEOs. Any decision involving market reaction can be simulated before execution.

How do you know whether a simulated scenario reflects what the real market would do?

The Galaxies platform validates the accuracy of Synthetic Personas against control groups of real respondents. The current benchmark is 91% accuracy. For high-impact decisions, the recommended process is to use simulation to filter hypotheses and, when needed, validate the winning hypothesis with complementary qualitative research.

The advantage of learning before executing

Every competitive market has companies arriving at the same decision point with different information. Some arrive with simulation data that reduced scenario uncertainty. Others arrive with feeling and outdated data.

Companies that test hypotheses before executing are twice as likely to outperform competitors in revenue growth over three years. The difference is not the decision-maker’s talent; it is the quality of information available when the decision is made.

For the CMO or CEO with a campaign, launch, or repositioning decision in the next 60 days: the cost of simulating before execution is a fraction of the cost of executing incorrectly. And the data will be available in 48 hours.