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What digital marketers can learn from corporate crises management

August 21, 2018

In the modern world, agile is better than big.

In 2016, Benjamin Gilad & Magnus Hoppe published “The Right Way to Use Analytics Isn’t for Planning” in the Harvard Business Review, arguing that the best ways to use analytics is “[generating] insights that in turn support ever-changing perspectives.”  He notes that many Fortune 500 companies and startups alike are over-reliant on old, aggregated data to generate static business plans.

That was published two years ago, yet we still find many companies today living in this same “set and forget” mindset - using data to inform the larger plan, but failing to adapt with dynamic insights to the quickly changing marketplace.

This kind of stagnant mindset leaves revenues, well, stagnant - even in growing markets.

But the result of management opting for historical, big data instead of real-time insights can be catastrophic. HBR cites several prominent examples within the last decade alone that exemplify the shortcomings of such rigid plans in unsuccessful product launches and poor crisis management.  

One of which was the India recall of Nestle’s Maggi in 2015, where the product was found to contain at least 7 times the permissible amount of lead. This resulted in half a million dollars of brand damage and a new market entrant victory.

In response, the author offers an interesting take on this catastrophe. He mentions that, “avoiding a $500 million mistake is surely just as valuable as launching a $500 million product.”

In other words, a penny saved is a penny earned.

In this case, the way to earn a penny (or 50,000,000 pennies) would be to generate both internal and external intelligence that updates with the ever-changing market. To act on dynamic behavior before crisis arrives.

How does this apply to digital marketers?

As much as overall business strategy must align with dynamic markets, online customer acquisition strategies must do so 10x. Because of all the data and tracking we’re afforded, digital growth marketers need to identify trends at a granularity 10x that of the overall firm, at a speed 10x as fast.

Here's just one reason why I say this.

In the past year, 20% of google searches were unique, compared to just 15% the year before. That’s a rapid increase in search complexity.

That means that the number of ways people discover content online is 33% greater than a year ago. And digital marketers must find innovative ways to make sense of real-time search data to not waste money on the wrong keywords.

This fact about google search only proves that people are discovering the internet through increasingly complex processes. Today, interacting with the internet looks like an incoherent conversation with a strangely intelligent friend. But there is sense to be made of it.

Businesses are constantly finding ways to meet consumers where they are, give consumers what they want when they want it. And in turn, consumers want even more. They demand seamless experiences. They will only discover brands on their terms - and in their (search) terms.

To make sense of these dynamic ecosystems, our advice here is for marketers to focus on unseen perspectives into the dynamic customer journey. In other words, marketers need to identify the behavior that leads consumers to discover their brands online. They need to know where their efforts will have the highest impact, and what efforts will make an impact on a visitor further down the funnel. They need tools that showcase the internet’s true architecture and consumers’ methods of content discovery within that architecture. Because wasting $100 of ad spend on irrelevant impressions is as bad as losing $100 of sales.

More data doesn't always mean better.

With some of the recent research coming out around overuse and potential inaccuracy of big data, it makes sense that not all business leaders love the idea of adding even more data to their daily lens.

Bob Nease even cautions that big-data can cast a dense fog in the modern marketers' decision making. 

In Fast Company’s “How Too Much Data Can Hurt Our Productivity and Decision Making,” Nease claims “we're left with our intuition when deciding what to do in light of all [the] new information. And that means that sometimes we’ll make things worse rather than better.”

We also find this to be true.

Currently, marketers working in the realm of search and display advertising use a variety of tools to view massive amounts of internet data. Digital marketers sift through google analytics to view search data, but with no clear recommendations for next steps. Without spending hours looking into what the data means, marketers can’t seem to make sense even a specific subset of search queries, let alone the whole ecosystem of competitive content.  

Making data both dynamic and actionable.

Data is only valuable when it offers actionable takeaways, and when its execution is continually put into context of the dynamic marketplace in which marketers execute. DemandJump does this by analyzing search data, website traffic patterns, and using machine learning to contextualize marketing efforts and quantify ROI.

This kind of dynamic intelligence provides a clear course of action supported by data. It affords individuals the power to make informed decisions and adapt to changing behavior, and still achieve business goals.  

While it is important to look at past data and learn from its analysis, there is greater potential in data when it can be used to show decision makers the exact actions they need to take and forecast the effect in the moment.  

Simply put, today’s marketers need to make data actionable, at all times.  

Aligning the business around dynamic data.

However, leadership’s buy-in to this kind of dynamic data is one thing. The next problem comes with the implementation of such a culture in the workplace.  

There is often disconnect between agencies, intelligence teams, and consultants working on strategy. And managers are forced to play office politics.  

HBR offers four steps to adopting a new business plan:

  1. manage talent differently,
  2. use competitive intelligence differently,
  3. work together, and
  4. study personal use of intelligence. 

In short, these steps should lead to altering the department, and company’s, culture to become more elastic, adaptable, and open to new ideas, creating a culture that not only encourages innovation, but precipitates it.

Institutional barriers must be abandoned for open collaboration between decision-making leaders and intelligence analysts. Actionable data is only as action-oriented as the company that harnesses it.  

If a corporate culture is one that ignores the new insights offered, then there is no benefit or ROI associated with actionable data.

Big data is useless until it is properly analyzed and becomes actionable.  Having big data leaves decision makers ultimately making a good or poor choice based on the past, ignoring present market conditions, competitive intelligence, and trends.  

Moreover, the data is often used for the creation of static business plans and rigid strategies, leaving little room for adaptation. Harvard Business Review concluded that data and analytics shouldn’t be about “making hindsight 20-20.”  In reality, it should be about making insight and foresight 20-20.

Knowing exactly what actions to take based on sophisticated analysis results in unprecedented ROI. It equips us all with the ability to optimize an entire go-to-market strategy, from research and development to sales and marketing.  

It is absolutely imperative that marketers’ strategies, and the platforms they use to execute these strategies, reflect today’s dynamic marketplace. If not, their companies will be wondering why they’ve achieved irrelevance.

Curious to learn more about this new type of dynamic analysis we’re talking about? See a demo of our platform to understand how we’re tripling ROAS for Traffic Cloud® customers.

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