StrategicDB helps businesses predict future sales and assess the impact of internal and external factors. Using predictive modeling, machine learning, and data mining, we identify trends and quantify business impacts across various scenarios. Predictive analytics can be applied to marketing campaign performance, risk assessment, start-up funding success, and operational outcomes. Whatever your predictive analytics needs, we can build tailored models to deliver actionable insights.
Predictive Analytics
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Predictive Analytical Services
Predicting the outcome of opportunities is essential for accurate pipeline estimation. It also supports resource planning and fundraising efforts. We can assist not only with opportunity or account scoring based on predictive data points, but also with broader sales forecasts to guide strategic decision-making.
Predicting how a marketing campaign will perform helps identify early signs of success or underperformance. From setting goals to understanding customer lifetime value, we help forecast marketing outcomes before it’s too late to make adjustments. As a marketing analytics agency, StrategicDB goes further by designing test strategies that validate and strengthen these predictions.
Predictive modeling goes beyond marketing and sales and can be applied to nearly any operational data. For example, it can be used for risk modeling in finance, forecasting output in manufacturing, or predictive human resource planning. Regardless of your predictive modeling needs, as long as you have data, we can analyze it and deliver actionable insights.
We partner with brands and agencies, big and small.
Frequently Asked Questions About Predictive Modelling Services
Predictive analytics in marketing, can be used in lead scoring, marketing attribution, segmentation, campaign optimization and calculating of customer’s lifetime value. Predictive model can help be automated in marketing automation tools utilizing data from model to build out real time prediction formulas within tools such as HubSpot, Eloqua, Marketo, and Salesforce Marketing Cloud.
We encourage to do testing to ensure that the prediction model is working as intended. It can be done for marketing campaigns where a small test is performed before rolling out to the rest. It can also mean running a small group via the model to ensure the results is as predict. It is also advisable to do testing instead of predictive models if the results are unknown and testing can provide the results that you are after. StrategicDB, a marketing analytics services company can help identify testing strategies and build predictive models.
The process of running predictive analytics is the same regardless of the purpose of running predictive modelling. The first step is to identify what is the outcome that is desirable or you are trying to predict it can be sales, marketing response in form of conversions or clicks, or can be another custom data point. Next is to look at all available data, and format it or prepare it for analytics. This can include data standardization or normalization, cleaning and remove data points due to lack of data and therefore unpredictability. Finally, you can identify the best method of model for your predictability. Then the model is run, and the results are tested on a smaller scale. If lack of data is established then strategies are provided to try to collect data from third party or from changes in internal processes.
We use machine learning to build predictive models and can also train your existing LLM models capable of running Python or R code to generate future forecasts. Our approach goes beyond a simple script that predicts sales. We create projection models integrated into dashboards that can be updated repeatedly, consider business-relevant variables, ignoring statistically insignificant ones and account for future business decisions that may impact results.
The cost of running a predictive model depends on the complexity of the model. If you are looking for predictive analytics model, insights and implementation, we can provide a detail quote.
StrategicDB is an analytical services agency, and utilizes AI and machine learning models to run predictive analytics. We then implement these models within CRM systems, marketing automation tools, and other platforms. Typically, we use Python or R, as well as statistical tools like SAS or SPSS. We also develop custom models using mathematical formulas. The specific tools or platforms are less important than applying the right methodology and leveraging the data available.
Typically once lead scoring is implement, it should be able to run for a few quarters. However, if you see that the funnel conversions are not consistent, or sales are not increasing, then it is time to test if the lead scoring is still working as intended. Otherwise, a yearly check-up is recommended.
Predictive models can forecast a wide range of outcomes, from sales to marketing spend and campaign effectiveness. The key is to go beyond simple predictions establishing a testing strategy, identifying potential impact areas, and running ‘what-if’ scenarios. For example, when launching a new product, predictive models can estimate the marketing investment required to achieve your goals. These models go beyond basic math, incorporating business decisions and market dynamics to provide actionable insights.