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Beyond Predictive: 4 Reasons for B2B Marketers to Consider Prescriptive Analytics in 2018 - MarTech Advisor

Beyond Predictive: 4 Reasons for B2B Marketers to Consider Prescriptive Analytics in 2018 - MarTech Advisor | The MarTech Digest | Scoop.it
In the first stage – descriptive analytics, past data is studied to learn from past behavior and to assess how it can affect future outcomes. The second stage – Predictive Analytics uses data to predict what could happen next. The third stage which is also often referred to as the final frontier in the Big Data analytics game is Prescriptive Analytics - where data helps prescribe different actions.

Here are 4 reasons for B2B marketers to consider Prescriptive Analytics in 2018 

1. Combines the best of descriptive and predictive analytics

2. Drives informed (digital) marketing decisions

3. Improves customer-focused strategies to enhance CX

4. Helps mitigate business (even Sales and Marketing) risks
CYDigital/marteq.io's insight:

Beyond Predictive: 4 Reasons for B2B Marketers to Consider Prescriptive Analytics in 2018 - MarTech Advisor

 

I'll wait for AI to come first...or when pigs fly.

 

This news comes to you compliments of marketingIO.com. #MarTech #DigitalMarketing

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What Exactly The Heck Are Prescriptive Analytics? - Forrester

What Exactly The Heck Are Prescriptive Analytics? - Forrester | The MarTech Digest | Scoop.it
"Any combination of analytics, math, experiments, simulation, and/or artificial intelligence used to improve the effectiveness of decisions made by humans or by decision logic embedded in applications."


Prescriptive Analytics Inform And Evolve Decision Logic Whether To Act (not not act) And What Action To Take

Prescriptive analytics can be used in two ways:

■        Inform decision logic with analytics. Decision logic needs data as an input to make the decision. The veracity and timeliness of data will insure that the decision logic will operate as expected. It doesn’t matter if the decision logic is that of a person or embedded in an application — in both cases, prescriptive analytics provides the input to the process.

■        Evolve decision logic. Decision logic must evolve to improve or maintain its effectiveness. In some cases, decision logic itself may be flawed or degrade over time. Measuring and analyzing the effectiveness or ineffectiveness of enterprises decisions allows developers to refine or redo decision logic to make it even better. 
CYDigital/marteq.io's insight:

Lots more when you CT. Brilliant.

 

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Predictive Scoring Is A Band-Aid -- Here's The Real Solution - Forbes

Predictive Scoring Is A Band-Aid -- Here's The Real Solution - Forbes | The MarTech Digest | Scoop.it
Here’s why prescriptive is the future:

1. It’s proactive, not reactive. Prescriptive platforms don’t require years of data in order to vet prospects. Past performance is just one variable of prescriptive models, and it’s combined with real-time data to leverage what your company knows — and what it doesn’t know — to prescribe your next customer. This requires prescriptive companies to not only create comprehensive, proprietary data sets, but to also expertly extract insights from them.

2. It’s people-centric. 

3. It’s contextual and actionable. They help your sales and marketing teams understand, in terms of personal relationships, why something is a “D” and not an “A.” This means that prescriptive platforms personalize recommendations based on individual sales reps and who they’re selling to, facilitating tactical exploration rather than a one-size-fits-all strategy. 

4. It’s the end of point solutions. Predictive solutions are often used in tandem with dozens of data vendors and automation tools. But with prescriptive, companies no longer need multiple models and tools for different purposes. Prescriptive gathers and analyzes data across product lines, segments, and sales reps.
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Prescriptive Analytics Adoption on the Rise - DataInformed

Prescriptive Analytics Adoption on the Rise - DataInformed | The MarTech Digest | Scoop.it
Data Informed: Please discuss the similarities and differences between predictive and prescriptive analytics.

Guy Yehiav: Prescriptive analytics is simply the next level of predictive analytics. More and more companies are now seeing the value of providing prescriptive analytics and are excited to adopt this approach.

The key difference between the two is that prescriptive looks at current pattern sets and provides actionable outcomes. Prescriptive allows a tailored approach for understanding both user behaviors and unlikely patterns that can cause organizations to lose money and waste resources. While both prescriptive and predictive analytics rely on big data for gathering and understanding customer information, what sets the two apart is who is assigned an actionable plan to fix the task.

Prescriptive solutions take predictive to the next level by providing a desired outcome and the right person to fix the problem at hand. Instead of relying solely on predictions based on educated guesses and past results, prescriptive analytics provide pattern seeking machine algorithms that promote positive customer experience and provide resolution.
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NEW: Experience Remarkable Planning Accuracy With New, FREE Growth Hacking Tool. Go here: http://goo.gl/UjcA8x  

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