Previous Work

Overall process and examples

As an agile consulting firm, we focus on what matters most: answering your critical business questions and uncovering insights that measurably improve performance across any metric that matters to you.

We apply proven analytical methods tailored to your organization's unique goals. Our lean approach to data analysis helps clients achieve meaningful outcomes without the excessive costs of enterprise-scale technology solutions.

Our Process
Descriptive, Prescriptive, and Predictive

Arrow graph illustrating 'Our Process' with steps: Descriptive - Identify opportunities for improvement; Prescriptive - Find a solution to capitalize on the opportunity; Predictive - Apply the solution going forward.

Example 1
Addressing Business Questions

Slide titled 'Addressing Business Question - Upfront' showing a bar chart of monthly percentage changes in traffic, paid traffic, big widgets, and small widgets from Jan 2019 to Apr 2020, alongside bullet points discussing exploratory questions, original assumptions, and answers about traffic impact on widgets.

Example 2
Answering Business Questions

Table showing correlations between sessions and users to Big Widgets with highlighted high correlations and p-values, accompanied by findings emphasizing stronger correlations for users over sessions and the importance of focusing on users rather than traffic for KPI analysis.

Example 3
Funnel Breakdown

Chart and table showing monthly unique visits, signups, and paid conversions from Feb to Jun 2016, highlighting a steady decline in signups until June when it rises again.

Example 4
Monthly Check Point

Digital Check Point report from December 2016 showing summary highlights of strong online sales growth and detailed tables with online sales, sales, visits, and leads data comparing 2016 actuals and status versus 2015, with green highlights on growth percentages.

Example 5
Modeling Results

Slide titled 'Predicting Sale – Model – Testing' showing a logistic regression equation, tables of variable coefficients and significance, summary statistics, and a red text box highlighting key insights about variables influencing sales prediction.
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