Our service, put simply
Even we have hard times understanding other software service providers when browsing their websites. We strive to be different.
goodmoves selects your marketing campaigns that maximize individual customer lifetime value (CLV).
goodmoves selects your customers whose CLV will increase the most for a given campaign.
goodmoves suggests customers and corresponding campaigns to avoid CLV decrease.
Prior to integration, we offer to statistically estimate the added value by running goodmoves on your historic data.
The AI within
We made goodmoves simple to use, by abstracting away its sophisticated form of artificial intelligence: deep reinforcement learning.
The challenge of campaign management is to:
Find the optimal strategy to choose time, channel, and campaign to contact customers.
Refine that strategy to match the individual needs of every single customer.
Expand the above strategy from a single to multiple campaigns to account for the interdependency of campaigns sent over entire customer lifetimes.
Adapt that strategy as fast as possible to the dynamics of the market and customer behavior.
goodmoves tackles these challenges by:
Taking as input the relevant context: customer profile, past interactions and current context such as competitor activity.
Suggesting an action based on individual context, such as sending an email with a bonus.
Comparing the customer’s response to prior expectations, and using any discrepancy to improve its strategy.
Repeating this cycle of observing, acting, and adapting to continuously improve its strategy of personalized campaign sequences. Read our non-technical overview for more info.
goodmoves creates revenue both by increasing CLV and by decreasing overhead.
A personalized, sequence-aware, and dynamically adapting strategy for a wealth of campaigns to maximize sustainable revenue streams.
Simply integrated via REST API, goodmoves finds and refines its strategy in a closed-loop fashion, removing the need for expert tuning.
With goodmoves, we target businesses with long-lasting customer relationships.
One of the largest network of municipal energy and water service providers in Germany
Finance and Insurance
Sparkassen Rating und Risikosysteme (subsidiary of Sparkassen-Finanzgruppe)
Our approach is shaped by our backgrounds in science.
We use a lean approach to build iterative minimum viable product (MVP) versions of goodmoves. In particular, we offer a customized simulation of goodmoves within a few days.
We verify goodmoves' added value against control groups at any time after integration - in particular, we validate simulation results.
We learn from MVPs and customize goodmoves to iteratively fit your needs.