How to Create True Brand Resiliency

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At this year’s all-digital Sitecore Symposium, Vijayanta Gupta, Sitecore’s GVP, Product Marketing, spoke about brand resilience and the tectonic shifts in consumer behaviors that brands must prepare for and overcome.

The reason brands become irrelevant, the reason they lose resilience, is not because they miss big changes. It’s because they miss the small stuff. There are changes in consumer behavior and changes in macroeconomics that hide under the surface until they become big, business changing movements.

The example he gave was Kodak. In July of 1969, Kodak captured one of the most historic moments in history – putting a person on the moon. Yet, in 2012 they filed for bankruptcy. How?

Many believe it was because Kodak must have missed the digital revolution. Wrong. Kodak invented the digital camera and was one of the largest producers in the world. What they missed was a tectonic shift in consumer behavior – why would I want to carry around both a camera and a phone when my smartphone takes decent pictures?

On the other end of the spectrum is Netflix. They realized that once high-bandwidth connectivity became widely accessible, consumer media consumption would take a radical swing. They anticipated the shift and reworked their entire business model even before consumer media consumption patterns actually changed. And they’re thriving because of it.

But how do you prepare for this? What are the tectonic shifts brands should pay attention to today? Gupta believes there are five.

  • Purposeful capitalism
  • Non-linear life
  • Customer ubiquity
  • Privacy
  • AI tension

Purposeful capitalism

Traditionally, capitalism has served one stakeholder – the shareholder. However, there’s been a realization that capitalism should serve all stakeholders, i.e. employees, partners, the environment, and, of course, the shareholders.

It’s important for brands to understand this because, as Gupta said, “Brands are a manifestation of creation of capitalism. Brands are how capitalistic initiatives capture customers’ mindshare.”

Customers want brands that are focused on wider stakeholder engagement and that have a purpose, not just a focus on profit.

It’s crucial for brands to listen to their customers and take action, even when the customers are not asking for or expecting it. Gupta’s example here was Procter and Gamble’s Pampers.

Last year, the photo below went viral. As a result, Pampers launched their #lovethechange campaign and committed to installing 5,000 diaper changing stations in men’s restrooms over a period of two years.

This photo wasn’t a direct outcry to Pampers, but they realized this was a problem they could solve and took action. By doing so they not only invested in solving a common problem, they created a moment of recognition for their brand and strengthened their brand resilience.

Non-linear life

The next macrotrend Gupta dissected is the emergence of a non-linear life.

For most, life used to follow a straight line – you were born, you went to school, you worked, you retired, you died.  

That’s not really the case anymore. Many are choosing to deviate from the straight line and are choosing what is being called a “multi-stage life.” In this model, perhaps you go to school, you take some time off to travel, you join the workforce before taking some time off to have a family, you become self-employed, go back to school, you retire, do some consulting work, etc.

It’s a very different, very unpredictable lifestyle compared to the former linear model. But why is this important to brands?

When customers choose a multi-stage life, the timeline for major life events becomes less predictable and how brands operate their business and remain relevant for their customers becomes far more difficult to measure against their customer lifetime value models.

These models are used to drive prediction around who will need what at a particular time. Brands must now take into account the fact that in-moment personalization could be more important than the data being collected from predictive models in terms of processing historical data and predicting the customer behavior.

An unexpected reality, sparked by COVID-19, is that many aren’t necessarily choosing the multi-stage life they’re leading.

It is predicted that the majority of the jobs that have gone away will most likely not return or, at a minimum, will not be the same when they do. And this has implications for brands.

Brands are built by two stakeholders – the customer and the employee. So with Microsoft’s prediction of 150M new jobs, specifically in the technology sector, brands have to be ready to help their employees through this transition. As a result, they’ve launched an initiative to help 25M people worldwide acquire digital skills.

They’ve invested in learning, unlearning, and relearning their customers and employees to make sure that their brand and their technologies remain resilient for the future and a multi-stage lifestyle.

Customer ubiquity

Dollar Street conducted a study that essentially highlighted the idea that what consumers use, brands they engage with, and what they aspire for is more dependent on how much they earn rather than where they live.

Customers are everywhere. This a fundamental mindset shift for brands to understand.

As Gupta says, “Customers do not demarket themselves as living in a developed world or a developing world and brands shouldn’t either.” When brands do that, they get a very myopic view of their addressable market and miss out on potential customers.

Privacy

There are between 30 and 50 billion connected devices in the world today and the reality is that for it to use us, it’s not necessary for us to use it. Read that again.

Technology has become invisible and, at the same time, perpetually connected. To allow a brand to monitor the things we’re doing in an invisible manner, we need to really trust that brand and be sure of what they will do with that data.

(Brands must be very careful not to allow themselves to be labeled surveillance capitalists; those who take data from someone without explaining to them how they’re going to use it and monetize it without their knowledge. Once you get labeled as such, it’s very difficult to bounce back.)

As many of us do, Gupta trusts Amazon. In Amazon’s Go store, you can walk in, pick a product, and walk right out. And while it’s incredible convenient, it should not go unnoticed how much data we’re willing to give away in exchange for that convenience.

From the moment you enter the store until the moment you leave, Amazon monitors, assesses, understands, and reacts to every action. That’s a huge amount of trust.

Brands must invest in “solving for this trust puzzle,” as Gupta says. This isn’t a regulatory compliance issue, this belongs at the c-suite level as well.  

Why? One bad move and you’re lumped into the surveillance capitalist bucket which impacts a brand’s ability to do business, it impacts the brand’s resilience to survive, and it impacts the brand’s relevance to their customers.

AI tension

The final tectonic shift Gupta touched on was balancing AI tension.

There has been a continued rise of algorithmic investment in personalized digital engagement delivery.

Algorithms are constantly operating to help drive personalized engagement and content consumption at scale, regardless of how social media platforms calculate your interactions.

As soon as brands start utilizing algorithms to drive engagement, they risk stumbling into the challenges that come with algorithmic bias. Gupta gave a great example here.

If you Google image search the word CEO, the top 10% of images in the top 100 are of women. However, in reality only 28% of CEOs are women.

Actually, when doing an image search, 57% of the job categories you find will show that women are underrepresented in the search results compared to reality.

The reason here is that the algorithm is biased because the data used to train the algorithm was biased. This becomes very clear once an algorithm amplifies this.

So, what are the brand implications? On one hand, brands must use algorithms to scale their personalized engagements and, on the other hand, they have to ensure they don’t fall prey to any bias that gets built into their algorithms.

The irony here is that the more algorithms a brand uses, the more they’ll have to rely on human judgment to eliminate algorithm bias.

Create brand resiliency

While these tectonic shifts may seem uncoordinated, they all converge at the consumer. But what can brands actually do?

You put the gears in reverse and work backwards. Start with the people at the center of the experience and work from there. Understand how their behaviors are changing, what tectonic shifts are taking place in their lives, and how that impacts their expectation of experiences.

Unsure how to move forward (or backwards in this case)? Content Bloom can help. For a free consultation, book some time to speak with one of our experts.


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