8 Ways to Keep the Rust Off of Brand Trust

We in the marketing and public relations business talk a lot about brand trust. Do we walk it? With trust, simply put, you have a chance to succeed with prospects and customers. Without it, well, you do the math.

We in the marketing and public relations business talk a lot about brand trust. Do we walk it?

With trust, simply put, you have a chance to succeed with prospects and customers. Without it, well, you do the math. In data-driven marketing, where data is often described as the currency of customer engagement, here, too, trust is the bank.

Right now, sad to say, trust appears to be available only at a premium. There seems to be less and less of it at a time when we really need more and more of it. This is societal. It’s not just advertising and business where trust may be in short supply. Government, institutions, education, medicine, media all seem to be scrutinized, with a loss of trust in the balance. At a time when and where factual information has never been so available and transparent, fears of misinformation, opacity, and malevolence also appear to be heightened.

Believability is at risk.

I can’t fathom how to regain trust in all these institutions just now. But I can think of our world of marketing. Brand, and brand trust, matter more precisely now, because trust everywhere appears in short supply.

Recently, Edelman, a global public relations concern, published its annual “Trust Barometer” report, looking at trust issues among consumers across eight nations, among them the United States. I find the results illuminating, because it helps provide a blueprint of where brands might concentrate efforts to bolster trust.

MarketingCharts.com summarized some of the findings here:

brand trust chart
Chart Credit: MarketingCharts.com, July 2019

(Re)Gain the Trust Some Insights From the Report

Here’s my take on eight areas of the findings:

Product Must Perform

While it’s increasingly a customer-centric world, product still matters. Quality, performance, convenience consumers won’t even entertain trust if the produce/service fails the bar. In fact, it’s the biggest trust factor. Reputation may enable consumer consideration, but 67% of customers report they won’t come back if the product fails. More than eight in 10 consumers cite quality, convenience, value, and brand trust as a “deal breaker” or “deciding factor” in a purchase decision.

Trust: Why Now?

Consumers report several reasons why trusting brands is more important: 62% cite concerns about product experience (can’t afford a bad purchase, need products to keep pace with innovation, and reliance on brands for increased automation); 55% about customer experience (use of personal data, use of tracking and targeting, and use of artificial intelligence in customer service); and 69% about societal impact (fake news and misinformation, brand involvement in social issues, and affinity with personal values).

Yet There’s Considerable Room for Improvement

Just 34% of consumers trust most of the brands they buy and use. While some might see this as in indictment, I choose to see it as a huge opportunity. In the United States, overall, 54% trust businesses to do the right thing trust in government, by the way, is 40% .

The Trust Dividend Is Real

When trust is earned, the payback is pronounced. The difference between not fully trusting brands and trusting brands for a long time is a 28-point lift in percentage when considering what brand to buy first; 33-point lift in staying loyal; 27-point lift in being an advocate; and a 21-point lift in defending a brand.

We Must Walk the Talk

Remember greenwashing environmental benefits? “Trustwashing” is also a concern regarding brands and authenticity. Worldwide, 56% of consumers feel too many brands use societal issues as a marketing tactic to sell more product. Trust in business vs. trust in government has fallen off year-over-year between 4% and 6% in brands’ ability to effect positive change on societal impacts. If you’re buying into social good, it had better be the real deal. That means an enterprise commitment that’s followed through rather than a marketing promotion.

Most Consumers Have Taken Steps to Avoid Ads

I think it’s a mistake to say all ads are held in low esteem they’re not. Other surveys have shown that eight in 10 consumers still rely on advertising to discover new products and services. But three in four consumers have taken steps in their lives – ad blocking, paid subscriptions, and changed media habits to curtail the amount of advertising they see. More than three-fourths of consumers says they pay attention to ads from brands they trust!

Enable Reviews and Influencer Involvement

Most consumers say they trust what others say about a brand, more than what the brand says in advertising about itself. Working in combination peer review then owned, paid, or social content (ads) can work together to lift trust.

Run Hard

Interestingly, the more saturated the message (meaning, engagement across media channels), the greater chance for trust. One might think this doesn’t square with the previous ad avoidance message, but it goes to show repetition and reinforcement work. But only when the message is on-point, resonates with the user, and conveys authenticity.

Conclusion

Those of us who worry and work a lot about “trust” we have some mighty work to do. But even in an age of consumer skepticism or simply skepticism the hard, honest work of trust-building often becomes its own greatest reward, regardless of business payback. Despite all the doubts and pushback, consumers do want to believe this necessary work is getting done, and brands and ourselves can be all the better for it.

Machine Learning: More Common Than You Think

There’s a lot of buzz lately about machine learning. In many ways, it’s transforming the consumer experience and improving the products and operations of many companies. Plus, it’s not just for data analysts — machine learning has real benefits in the lives of the average consumer.

[Today, Sue is hosting Sanjay Sidhwani, SVP of Advanced Analytics for Synchrony Financial, as a guest blogger for The Consumer Connection.]

There’s a lot of buzz lately about machine learning. In many ways, it’s transforming the consumer experience and improving the products and operations of many companies. Plus, it’s not just for data analysts — machine learning has real benefits in the lives of the average consumer.

Ever wonder how Netflix serves up recommendations for the next movie or how your smartphone knows that you will be driving to work on Monday morning? Those are both examples of machine learning.

How is machine learning different from ordinary analytics? With traditional methods, an analyst defines the objective and looks for correlations between the objective and a defined set of data inputs. If new data comes in, the analyst needs to rerun the analysis and create new correlations and a new algorithm. This can take a while.

Machine learning is more efficient because it automatically takes new data inputs and adjusts, or “learns,” without manual intervention. So, the impact is immediate. How is it learning? The behavior drives the operation, not the programmers. Netflix recommendations are a good example. Once you watch a program or a movie, the next set of recommendations are created automatically without adjustments from an analyst.

Let’s take another example. Say you are considering buying a used car. What’s a fair price? Many factors determine this, such as age of car, miles driven, model and make. With enough data, we can infer the relationship between these factors and the price. This relationship can be linear, where the attributes have an additive effect (e.g., miles driven). But often the relationship is not linear. A car’s age, for instance, has a geometric effect on price (15 percent lower each year). In machine learning, the nature of these relationships doesn’t have to be a total guess. The programs automatically adjust these inputs and give us a fair price.

Machine learning can also help companies market offers more efficiently. One way is pattern recognition. There are patterns in customer buying behavior, for instance. Machine learning algorithms can predict the next likely item to be bought, helping a brand decide which customer should be targeted with what offer, better addressing their needs and wants and eliminating wasteful and costly marketing.

The challenge for companies is how to implement their learnings. What to do with the prediction — offer a discount? Display on the website? Send an email? The key to making the data impactful is “closing the loop” and refreshing the learnings so the data leads to actual behavior.

There is a budding community of data scientists and analysts who are exploring machine learning techniques. I recently attended a hackathon on Artificial Intelligence in our Innovation Station, a technology hub in our Chicago office. Most of the teams’ ideas used machine learning techniques combined with new types of data, such as facial recognition of an applicant’s LinkedIn picture to authenticate digital credit card applications or building a neural network chatbot that provides personalized service and account analytics.

The possibilities for marketers are exciting and endless. As we learn more about the technology, the real-world applications are likely to grow and provide even more value to brands and consumers alike.

Note: The views expressed in this blog are those of the blogger and not necessarily of Synchrony Financial.

Hype or Opportunity? 

Marketers today face the huge challenge of creating the right program mix to meet their brand objectives. It’s difficult to balance the risk of new investments against the budget support needed to continue in proven channels. But it could be even riskier to wait too long to test or adopt some of the newer opportunities that emerge with oppressive regularity.

Marketers today face the huge challenge of creating the right program mix to meet their brand objectives. It’s difficult to balance the risk of new investments against the budget support needed to continue in proven channels. But it could be even riskier to wait too long to test or adopt some of the newer opportunities that emerge with oppressive regularity.

The bounty of options makes planning more complicated and can thinly stretch even the largest of budgets across a wide array of team efforts. Each team effort must be supported with planning, development, distribution, optimization and reporting, all of which cost time and money. And though more options generally leads to more learning, it also creates more work — and sometimes even a dilution of impact upon prospects.

Some of those new opportunities will earn key positions in future campaigns via their proven contributions to specific objectives. But many will turn out to just be a shiny object that got its fifteen minutes of marketing fame and ate away your resources. One handy tool to help you hedge this high-stakes bet is the Gartner Hype Cycle.

Gartner has been publishing this annual review for many years. It considers emerging technologies in a way that best informs critical business investments. It offers brands distinct interpretations of real value versus hype, charted along a continuum marking the highs and lows of technology adoption over time.

The cycle begins with a peak of inflated expectations, tied to a wave of adoption and a lot of market attention, before negativity and failures lead to a trough of disillusionment. Then the real work begins: adapting best practices and methodologies that lead to higher productivity. Rinse and repeat.

Hype CycleThe 2016 Gartner Hype Cycle of emerging technologies highlights three big trends, including:

  1. Immersive Consumer Experiences, like virtual reality, smart materials and gesture controls
  2. Smart Machines and workspaces that foster the evolution of the Internet of Things and digitize physical objects to improve efficiencies.
  3. Technologies that connect to each other and synergize previously autonomous technologies and platforms.

Gartner actually publishes multiple hype cycles annually. Some of these cycle reports focus on particular technologies, so if you have an interest in a specific area of technology, you should do some further digging.

It is easy to see how today’s technological innovation can evolve into tomorrow’s marketing tool kit, but it’s not a quick, direct or easy journey. Watch for the phases of the hype cycle but also for the availability of tested vendors, channels or service partners to help ease your adoption. Most marketers are not equipped to leverage the raw technology on their own, so they search for partners with a tested offering that effectively employs the emerging technology. But this typically occurs in the later stages of the hype cycle, which in some cases may be too late.

So how do you know when it’s time to jump in, and how do you maximize the impact of your inherently risky choice?

  • Have clear goals and benchmarks in place, along with a time frame to assess whether this new initiative is achieving its function within your plan.
  • Know the difference between technology and marketing. Both have value but they are not interchangeable.
  • Don’t launch what you can’t measure.
  • Some endeavors are more labor and research intensive than others, or further outside of your comfort and experience levels. Weigh the effort expended against the potential return before embarking.
  • Build in additional time. New efforts always need additional launch time, QA time, etc.
  • Fund the effort appropriately. Just dipping your toe in may not return a realistic picture of the actual value.
  • Know what your team resources can support. Unduly stressing them can have unintended negative consequences on unrelated programs that had been running smoothly prior to the adoption.
  • Keep a balance in your budget of proven tactics, but also set aside a testing budget so as to continually learn and freshen your eye.
  • Don’t hang out on the bleeding edge unless your brand and your audience are already there. Not every new marketing opportunity will be a good fit.
  • Do your research. You can learn a lot from watching early adopters.

Success today favors the bold but informed. Make smart choices, and continually test and refresh your marketing mix. Maximize the opportunity and minimize the hype.