Customer churn, pricing strategy, sales analytics, ... these common tasks are where managers spend most of their time and also prove their skills as a strategist.
General purpose solutions are rarely the answer. For instance CRM tools offer a range of factory settings for analytics/visualization, but they're quite limiting and rarely adapted to the problems at hand.
As a result, managers spend a great deal of time conjuring reports, graphics, presentations ... with office applications.
With over two decades of experience in business environments, I realize the importance of giving a purpose to data: from reporting to stakeholders to transforming it into concrete and informed actions.
What can data science do for your business:
Data Storytelling: Shiny Apps give a narrative to your data, showing it in a way that makes sense and leads to concrete decisions.
Time-savvy: cutting down your usual reporting time from minutes or hours, to mere seconds.
Deliverables: R-Shiny app for real-time analytics, R Code to process/export your reports, detailed user guide so that you can replicate the process over time.
Example of a Pricing Strategy:
- Be realistic
- Provide for worst- and best-case scenarios
- Show profitability and type of revenue to the investors (share of recurring vs. one-off)
- Make sense to the customer
- Align with the competition
- Allow your staff to exceed sales targets and optimize commission scheme
- Factor in internal costs (service/support/…) and predict a reasonable break-even point
- Optimizing the pricing policy is within the remit of seasoned managers who usually end up with complex spreadsheets and a headache.
- There is however a scientific approach behind it that combines existing models (skimming, competitive, penetration, …), your positioning within your industry, your economic realities, statistical concepts and predictions.
- There is no one general purpose product or one-fit-all excel table that can help you with all these aspects.
- Audit of your current pricing, identifying levers, challenges, ...
- Building a customized app where you can tweak all parameters and immediately visualize the impact and outcomes
- Analytics and recommendation of several possible pricing scenarios
- Setting quantifiable revenue goals
- The customized app is made flexible enough so that you can reuse it over time whenever you need it. This way, your pricing policy will be based on data, factoring in real economic and market realities.