Digital analytics are increasingly important. Gone are the days of running a marketing campaign by the seat of your pants or using vanity metrics alone to guide marketing decisions. Today’s marketers need to step up their game with new BI (business intelligence) skills based on sound marketing concepts.
I recently started a course offered on Coursera by MIT on analytics using R. It’s a little cumbersome to learn after using SPSS and SAS, but, heck, it’s free and offers some visualization options missing from these more powerful and expensive options.
Of course, we can’t forget text analytics, which, according to IBM represent 80-90% of all data generated. Attensity handles these analytics and produces visualizations to help plan better marketing strategies.
Digital analytics: weekly recap
Google and Adobe leading digital analytics
An update from CMS Newswire by Pierre DeBois highlights how industry leaders, Adobe and Google, are changing the very nature of digital analytics:
All of these changes complement the current consumer-centric era. The behavior of empowered customers, instead of brands, drives influence.
Just consider the established practice of showrooming, the customer comparison of a product online while standing in a store location; parallel device usage among consumers while researching online, and high expectations for personalized marketing that speaks to the individual’s needs.
Adobe and Google are responding to these trends. And these changes will influence the ways marketers organize, unraveling traditional marketing strategies.
They will also drive a potential shift in analytics strategy.
Digital strategy (and thus, digital analytics) are becoming more customer-centric — employing the longstanding marketing concepts of “The Customer is King” to the digital age. No longer should businesses plan marketing communications that are easiest for the brand, but best for the consumer. No longer can businesses operate with their traditional media and digital media strategies and tactics out of step with each other, but must provide a single, integrated marketing strategy spanning traditional and digital media.
This requires a deeper knowledge of the customer and integration of this knowledge from UX and product design, through sales and marketing.
Changing digital analytics landscape
Google digital analytics and you’ll find pages of available jobs for digital analytics professionals and training courses, which replaced what you would have found only a few months ago — tools and articles spouting the importance of analytics for building and maintaining your brand.
I personally find this shift significant. Instead of trying to convince brands they need digital marketing, 1st page belongs to firms trying to hire professionals with the training necessary to carry the analytics load of their brand.
Translation — everyone now recognizes the importance of analytics. It’s a given. The challenge now is finding the right people to provide guidance. As a marketer, that means retooling to have the skills necessary as the new paradigm of marketing emerges.
Predictive analytics reflect just one process forcing brands to step up their analytics game. As I’ve discussed on this blog many times, predictive analytics rule by providing not only descriptive analytics showing a snapshot of where you are, but offers strategies likely to IMPROVE where you are.
This week, Marketing Land published 3 case studies using predictive analytics to improve ROI.
Predictive analytics can help you use past data to predict likely future outcomes. While these techniques have long been used in forecasting, risk aversion, and even fraud detection, in the digital world, predictive can be extremely powerful.
These days the amount of digital marketing data and the availability of enormous processing power make the application of predictive analytics in the digital marketing space particularly exciting. It can be used to predict a likely lifetime customer value or the probability of customer loyalty or churn, and predictive techniques can also be used to gain insights into the best ways to allocate marketing budgets or understand the likely effectiveness of potential campaigns.
In their post, they point to 3 ways predictive analytics help improve marketing outcomes:
- Predicting where to place your ad spend to maximize returns
- Leveraging your A/B testing to generate the highest ROI
- Learning where NOT to spend money
In addition, predictive analytics help:
- segment customer markets to optimize return and minimize expenses
- build better products through part-worth determinations
Digital marketing analytics mistakes
MarketingProfs published a post dealing with the top 3 digital marketing analytics mistakes brands make.
Mistakes in analytics lead to poor marketing decisions and spell danger to the firm. Among the mistakes identified by Joshua Reynolds in this post are:
- Not aligning analytics with KPIs. It doesn’t really help to include metrics that don’t map to a firm’s KPIs (of course, this assumes you’ve got a pretty comprehensive set of KPIs not just bottom of the funnel stuff like sales). This is why vanity metrics, including Facebook Likes and Twitter Followers, have little value for a firm. Sure, they HELP contribute to positive KPIs, but the link is pretty tenuous and non-linear. You’re better off paying attention to metrics with a stronger link to KPI, such as conversion from your community or from a social visit.
The only thing worse than the wrong answer is the right answer to the wrong question. We often see marketers that are married to their theories and hunches, using analytics to confirm biases rather than to explore alternatives.
The way to avoid the wrong question is to let your data whisper to you and engage in an iterative approach that provides the ability to adjust an inquiry as the process moves forward. Sometimes, patterns in the data may be surprising.
- Expecting data to provide answers. That’s not gonna happen. Instead, data are the starting point for exploration and curiosity — what if … You first have to get down to the source of the problem and find the solution; not just view the data, but what’s behind the data. That’s why you need marketers in charge of analytics. Their understanding of markets and marketing concepts allows them to ask the right questions, rather than expect a miracle from the data.
In addition, be sure your data is clean. Sometimes researchers forget that data can be contaminated or not downloaded properly so the data table is nonsense.
Digital analytics tools
Great tools exist to help analyze and visualize your data. Incredibly, Google Analytics is FREE and a great wealth of information on digital marketing returns.
Many tools exist and some are incredibly expensive (but powerful). Others are free, such as insights from your social networks.
If you’re looking for free and inexpensive tools, here’s a great list from Loves Data, especially for Not For Profits firms.
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