Why do you need Marketing Analytics?

5. Personalisation throughout the marketing funnel from awareness phase to the advocacy phase

Marketing funnel demonstrates how to target prospects at different stages with different tactics. As prospects enter or exit at any stage of the marketing funnel, one-message-fits-all is no longer applicable. Meet the customer expectations when they reach out to you by matching purpose with their intent. Choose the right strategy depending on the stage they are in: discovery, engagement, conversion, retention, etc. Provide unique, personalised experiences for each buyer to attract new customers and create loyal brand advocates.

6. Optimise Net Present Value: find the balance between ROI, ROAS, CAC and CLTV

Enhance your marketing cloud to manage the entire customer lifecycle. Bring together data from all touchpoints to understand the customer journey, predict marketing outcomes, and personalise across all touchpoints. Prioritise targeting and flow based on Net Present Value instead of on short term conversion. Reduce Customer Acquisition Costs by targeting a new customer only when it is profitable against Customer Lifetime Value. Grow reach at the same acquisition costs by smart spending and ROI optimisation.

8. Apply any kind of modelling from the Google AI platform or any other analytical product

AI Platform allows you to easily create, produce and deploy machine learning projects without lock-in to get a clearer picture of how customers will engage with your business. The integrated toolchain helps you to manage all stages in the machine learning workflow including training ML models on your data, evaluating model accuracy, tuning hyperparameters, deploying, sending prediction requests to your model (online or batch prediction), monitoring the predictions on an ongoing basis and managing your models and model versions. AI Platform offers advanced tooling to help you understand your model results and explain them to business users.

9. Future proof on speed, flexibility and security

Benefit from a flexible and secure framework of Google Cloud to build what you need at a pace that matches the industry. Solve your marketing challenges with marketing analytics technology that enables:

Fast development cycles to quickly develop successful experiments into business as usual.The more visibility and monitoring there is in place, the easier it is to grow, innovate and save costs.
No heavy maintenance workload for your teams so that you can focus on strategy instead of engineering.
Capturing the effects of A/B testing audiences will generate learnings about their profile which we can use for targeting future campaigns
Centralised user management allows for more simplistic and tighter security9.

10. Use less separate tools for your marketing activities

The diversity of today's marketing technology combined with the broad set of tasks that marketers need to tackle caused that many marketing teams have reached the point of tech-overload. It has become very time consuming to apply analyses and models to get all the customer information from the data. Once organisations start seeing insight from their data powered by cloud technology, they want to make it faster, easier and smarter. They want to activate the data, apply machine learning and build prediction models to create delightful customer experiences.

Why do you need Marketing Analytics?

1. Measure user interaction across different owned and paid channels, apps and platforms

2. Measure interactions across the ecosystem of advertising platforms

3. Activate insights from data back into the platform in a timely manner

Benefit from providing better customer experiences by using the power of both Google Cloud Platform and Google Marketing Platform.

4. Activate one campaign across all marketing channels

5. Personalisation throughout the marketing funnel from awareness phase to the advocacy phase

6. Optimise Net Present Value: find the balance between ROI, ROAS, CAC and CLTV

There are a couple of things we can build for you to deal with these challenges successfully:

7. Integrated data without engineering

8. Apply any kind of modelling from the Google AI platform or any other analytical product

9. Future proof on speed, flexibility and security

10. Use less separate tools for your marketing activities

Ready to start?

Amsterdam

Rotterdam Office

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