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Paralysis by Analysis: Secrets to Overcoming Predictive Analytics Challenges

Secrets to Overcoming Predictive Analytics Challenges

Transforming customer experience requires response to an organization’s intent with the right level of engagement, the right message, and the right allocation of resources to convert them to pipeline.  However, attempting to consistently extract details of your current engagements with your top accounts and deliver that to the database of new demand units within those accounts, is a colossal task.

This is where predictive analytics takes center stage. Predictive analytics provide an automated visibility into the intent of your target market, reaching beyond your top account segments. Knowing what prospects are attracted to, allows you to deploy the messages that will have the most impact, and the tactics that will be the most effective. Yet some firms are still not capitalizing on the power of predictive analytics, struggling to overcome challenges and missing out on key opportunities.

Bridging the Skill Gap

A scarcity of talent can be the first challenge organizations face, as predictive analytics solutions were historically designed for data scientists with a deep understanding of statistical modeling. Although vendors are making it easier to build models using automated predictive modeling tools, it’s one thing to build a predictive model, however in order to trust the model, you need to understand whether the model is meaningful. That means having the skills to know how to interpret model metrics.

The last thing you need is another data source, right? MRP platform architecture is centered around the ability to both identify actionable data, like predictive analytics and Intent data, and automate workflows that action this time sensitive data on the fly. Instead of ETL, or data normalization, deduping and onboarding, MRP clients now focus on their market expertise because they no longer need to manage a team of data scientists.

Desegregating Silos

New technologies can be difficult to integrate, which is why end users are nervous to adopt it until the inevitable teething troubles of a new system have been worked out. Predictive analytics solutions typically live as standalone tools that don’t integrate with the existing technical infrastructure of enterprise-class organizations. Problems with integration often leads to predictive analytics solutions being housed in a silo separate from the work its intended to influence.

Through hundreds of conversations and deployments, we learned that enterprise-class organizations have varied needs to use existing technical infrastructure, source new or even deploy some functionality on a managed service basis. MRP Prelytix is designed around such a use case, providing clients the flexibility to deploy programs at any point in this continuum, or a hybrid combination. For example, many clients will connect MRP Prelytix to their CRM and Marketing Automation systems for data management and execution purposes yet use our DSP to deliver ads and marketing automation systems to manage micro campaigns.

No Blackbox – Observe the Intent of Your Target Market

Traditional approaches to analytics rely on batch processing, where data is scored based on a schedule. These approaches are inherently re-active because their focus is on aging data, meaning organizations are only able to react to past activity. Traditional architecture also limits a business’s ability to mirror the movement of the market, due to their difficulty to efficiently manage and track the consumption of data streams.

Your target accounts move fast, your predictive assessments need to move faster. MRP Prelytix is the only Predictive Analytics platform to escape from typical static batch processes, giving our clients a head start to reach and engage each target account before the competition.  Mirror the movement of your target market and measure conversion rate by tactics, segment, region, and marketing resources, to continuously make your next prediction smarter. MRP Prelytix allows you to see how your campaign performed within a specific time frame and determine if adjustments are needed moving forward.

 

 

 

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