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Marketing Myths and Predictions

By Nick Price



crystal ballThis week Drew Hendricks, writing for Forbes, chimes in with predictions for Big Data in 2015, attributing growth to access, technology and analytics on the rise for businesses of all sizes.
We agree that most of these technologies are happening and will be more prevalent in the new year:

  •      Retargeting “exploded in popularity” in 2014 and is on the rise for 2015, as data can be gathered on a site’s visitors, products viewed and purchases made—and then used to engage customers during the buying cycle and across other screens.
  •      Custom Dimensions or Custom Variables—businesses can gather customer and demographic data, as well as business data to create relevant messaging.
  •      Marketing Personas—targeting customer types will inform content marketing campaigns.
  •      Customized Paid Campaigns will allow professionals to determine their target audience before a paid campaign; and then measure results and modify accordingly.
  •      Offline and Online Merge. Big data, from sophisticated heat map camera systems to beacon technology, will inform real-world transactions. Web and in-store performance will be adjusted and marketed accordingly.
  •      Personalization. Big data will guide the customer’s online shopping experience with suggestions based on previous interactions, customized emails and targeted messages.

Predictive analytics, using this data to determine how to address a customer’s needs, is included in year-end predictions, as above. As with anything great and mighty, certain folklore emerges. Angela Housman debunks some of the myths of predictive analytics in
Here are some of her highlights:
Myth 1: Predictive analytics is easy. Anyone can do it.
You can’t just throw it together and let the machines sort it out. “Predictive analytics requires some serious training in consumer behavior (at least within the marketing area) as well as alignment with company goals.”
Myth 3: Only what you measure matters.
Not always so. Intangibles, such as trust, go into buying decisions as well as historical data.
Myth 4: Correlation = Causation
“Predictions are primarily based on correlations (relationships) between the data you have. But, correlations don’t mean that one factor CAUSED the other factor.”
Myths 5 & 6: Predictions are perfect…or forever.
All the data in the world can help produce a probably outcome, but there’s no guarantee. Also, when new data is available, it should be factored in.
Myth 7: Only a paid professional can implement predictive analytics.
Not so. Predictive modeling requires a skilled analyst, thorough understanding of what data can be collected, the organization and campaign goals. This is often an employee within the company.
Myth 10: Insights = action
Not so again. Insights inform actions, but need stakeholders to move it forward.
All of these rely on the advanced analytics that are more sophisticated at gathering, parsing and communicating customer data. Adding the human touch to big data will always help improve on any speculation.
Image via Jlhopgood

Nick Price

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