Anticipate Customer Behavior for More Effective Digital Marketing
Data science gives you the power to increase operational efficiencies and get more from your marketing investment.
Imagine knowing exactly how much effort your sales team should exert on specific clients or the perfect way to personalize a customer journey based on existing Customer Relationship Management (CRM) information.
Using applied statistical methods, such as regression and decision trees, we can build predictive attribution models, so you know exactly which methods and techniques are having the most impact. Cluster analysis uses the behavioral and CRM data you already have to discover the specific customer segments that are unique to your business, giving you a competitive edge.
Our tailor-made customer journey dashboards make it easy for even the most qualitative team members to utilize actionable insights across segments, helping to both balance and prioritize revenue potential and acquisition cost.
How We Help You Gain More Advanced Insights with Applied Statistics
Make a positive impact on your bottom line with applied statistics, advanced predictive modeling techniques, and deeper insights. Whether you’re engaging with Evolytics to build the foundations of a data science program, augment your advanced analytics team, or simply want a world-class analysis partner, our predictive analytics consulting services will add to your organization’s knowledge base.
Our most common client requests include:
- Building predictive models
- Uncovering product development insights
- Creating personalized recommendation engines
- Segmenting customers through behavioral analysis
- Interpreting large voice-of-the-customer (VOC) data sets with natural language processing (NLP)
- Building forecasts
- Creating attribution models to explain how impactful a tactic may be
- Data engineering and ETL for data science initiatives
- Market basket analysis
Our data science team uses a variety of advanced statistical and machine learning methods, such as: factor analysis, cluster analysis, hazard analysis, perceptual mapping, decision trees, and regression analysis to answer your most important business questions.
We also offer our expertise using Python, R, SAS, SPSS, and Alteryx, which make us ideal partners for helping write analytics code, deliver documented outputs, and provide customized team training.
Our Data Science Consulting Services
Predictive Analytics and Statistical Analysis
We use data, statistical algorithms, and machine learning to help you make business decisions and targeted digital marketing efforts based on potential outcomes. Predictive and statistical analysis put you ahead of your competition by anticipating customer behaviors and actions so you can answer questions and create a better user experience as you lead them to purchase your product or service.
Statistical analysis can inform your decisions and help you understand if those directional insights you’re seeing in your Business Intelligence tool are real, reliable insights. Machine Learning mines your data to discover more insights, more quickly than any analyst could on their own.
With propensity modeling, you can predict the likelihood of a visitor, lead, or current customer to perform a certain action on your website (i.e. browse your site, click a CTA, pick up their phone to call). We employ a variety of machine learning, data science techniques and ultimately choose the one with the best fit and predictive accuracy. These insights help you anticipate customer behavior and create a user experience that leads them further along the sales funnel.
Once you can anticipate future customer and user behavior, you can plan for possible challenges and obstacles you’ll need to help that customer or user overcome. We help identify these challenges and obstacles for you based on reliable, statistical analytics and work to strategize future initiatives to meet that user’s need and lead them to a conversion.
We can help you with scenario planning too, predicting what potential changes in your marketing mix may do to your traffic or conversion forecasts.
Forecasting has been especially important during COVID-19 planning, bringing up critical questions, such as:
- How much has the pandemic impacted your business?
- What else is influencing your customer behavior right now?
- What can you anticipate for the upcoming season?
- How will you forecast against these numbers next year?
While there are no easy answers, our team of statisticians, data scientists, and business analysts are already building predictive analytic models to answer these questions on behalf of our clients.
Market Basket Analysis
You’ve probably heard that Target can predict pregnancies through data science and have used that knowledge to better target expecting families. Imagine having that type of behavioral knowledge and being able to serve the most relevant product to your customers.
Product Affinity analysis tells you which product to suggestively sell based on a customer’s current or prior basket.
Understanding market basket behavior like this gives you an advantage in creating cross-sells, upsells, and product list view pages. Market Basket Analysis can also help you determine the best revenue-generating strategy for your business line and customer segments: cross-sell, upsell, frequent small purchases, or infrequent large purchases.
Working with our A/B Testing & Experimentation team can help you apply the perfect method to each customer.
Data Mining for Hidden Insights
Data mining is an effective data science solution for identifying patterns and correlations within your data sets to predict future customer behavior. Understanding these patterns and anomalies can help you take steps to increase revenue, cut costs, reduce risks, and improve the customer experience and relationship with your business.
Some data mining processes, such as Recency, Frequency, Monetary (RFM) models are somewhat basic but can make big differences for a retailer. Others may be more exploratory in nature but generate a true strategic advantage that your competitors can’t easily copy.
Machine Learning and AI Investments for Greater ROI
Gain powerful insights into your customers with machine learning through artificial intelligence (AI). Just like Google and Facebook are able to know more about you based on your digital habits and footprint, you can use similar machine learning applications to understand your customer more. This knowledge will help you better market your products and services to them.
It’s important to understand as you consider AI that it is a significant investment. AI requires a robust data architecture, clean data to ingest (and a lot of it), automation processes, and time to test.
AI failures can be costly and may come with bad PR. Have you heard about Amazon’s biased hiring practices, IBM’s Watson Oncology results, or Microsoft’s Twitter bot? While these companies should be applauded for their trendsetting efforts and willingness to fail, you don’t have to repeat their mistakes.
Our team of data scientists and data engineers love collaborating with innovative teams to create the right AI roadmap—from infrastructure setup to testing into success.
Data Science Model Management
If your data science program relies on one talented unicorn, you’re not alone. While this is a common problem among enterprise businesses, the unicorn data scientist method isn’t a scalable or efficient one.
At Evolytics, we piloted Model Management with our own team for the College Basketball Predictor using GitHub and Anaconda. Then, we began working with clients using AWS Sagemaker to automate daily predictive analytics models to fuel marketing platforms. Now we’re ready to share our data science model management learnings with your team to ensure anybody in your organization can run any code from any machine. No more “runs on my machine” excuses or single-point-of-failure dependencies.