Predictive Analytics

Predictive analytics is about acting rather than reacting, filtering the signal from the noise and looking ahead with confidence. And let’s remember, the voice of the customer is by no means limited to quantitative data – also called structured data. Nor is it limited to internal company data. So, what are we really doing with the technology? Once we pull all the data together, we can begin to categorize the processes that need to be taken to hear the voice of the customer. The processes may include empirically derived models for predictive or prescriptive analytics.

The results are that you can better predict customer preferences and buying patterns. Although our goal is to see the customers as individuals, patterns may emerge from the data that may give you some additional insight into clusters of customer types that might for example receive a certain offer.

Customer contact patterns are changing – there has been an explosion in contact channels. And people are more comfortable sharing so much about themselves, by and large.

They are comfortable because they understand the dynamic between the information they possess and the value that they expect in return. But they expect personalization and customization in return for their information.

Next Best Offer

Well if you know the individual and you know their buying patterns, and you know what they might need next, you begin to predict what they will do next. This gets us into the world of predictive analytics.

Next Best Action

A related trend is Prescriptive Analytics. Some might think that it’s the same thing as Predictive Analytics. Well really, it’s not.

Think about Prescriptive Analytics within the context of Next Best Action. Prescriptive Analytics is just that – how can we prescribe to you – not just offer something to you – but prescribe to you what you ought to do – and it may not be in service of commerce but it may be in service of enhanced customer experience.

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Supercharge advanced analytics

We align knowledge workers to assess and implement advanced analytics in marketing, finance and operations.

Changing consumer behaviors and innovations in big data, artificial intelligence, and machine learning—chief marketing officers and their peers must transform how their organizations go to work.

We provide folks that have firsthand experience from the world’s leading technologies and industries players to help companies rise to the challenges of using the most recent advanced analytics tools, processes and techniques.

As we know, personalization makes our customers’ lives better and increases loyalty by delivering messages that are fine tuned to anticipate what customers really want.

Capturing value from personalization, however, requires more than technology. It requires an approach that brings the right people at the right time to move your initiatives forward pragmatically.

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Identify & Expand

Identify opportunities for advanced analytics improvements, expand the data ecosystems available both internally and externally, and enable new insights ability, leveraging high-value technologies. Business Analytics can deliver disruptive results without disruption with an enterprise AI platform. Fused internal and external data feeds the fire for innovation. Focus on actionable archetypes that can drive short term improvement with micro-demand forecasting, while concurrently identifying emerging and waning trends with the enterprise AI platform. Enterprise AI is changing how business value is unleashed at an unprecedented pace. It is transforming core processes and business models in every industry. AI for the enterprise is changing the rules by discovering perishable opportunities hidden in diverse data. The quantifiable success of business analytics relates directly to aligning it with Enterprise AI – an intersection between people, the ontology and the business outcomes.

Build & Integrate

Knowledge workers select the best models and approaches, ranging from modeling algorithms to advanced machine learning, applying industry knowledge. User-friendly tools are then integrated. Leveraging existing data where it sets today, along with select third-party data, stunning use case yield optimization can be achieved. Rapid, automated actions are ultimately federated to knowledge workers through existing systems. Micro-segmentation can create a holistic understanding of customer drivers, preferences and behaviors – at times for which experience opportunities are perishable. The symbioses between data science and artificial intelligence (AI) demands knowledge workers aligned with the way enterprises need to understand their customers - and with AI solutions that impact the bottom line. Adaptive optimization provides enterprise yield, an AI-enabled discipline, enabling stakeholders to identify perishable opportunities across a myriad of business use cases.

Create & Optimize

Data engineers, data scientists, software engineers and consultants create the data architecture and governance to capture the potential of advanced analytics. We'll help prioritize use cases that have near-term impact on the most important current bottom line levers, such as improving customer loyalty, driving operational efficiency, optimizing resource allocation or increasing purchasing frequency as a few commonplace examples. Business analytics and enterprise AI alignment naturally narrows the gap the between your current and desired future state of advanced analytics. But equally as important, connecting the dots on a pragmatic yet powerful business model lets the tech do its magic with breathtaking results. These use cases are varied across industries but share a common trait of fused internal and external data, providing cross-enterprise yield optimization with a rapid, automated action. Goal-driven yield is guided by human creative, the brain-power judgement of people.