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Author
Derek Slater, Ready State Derek Slater, Ready State
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2022년 09월 13일

7 Things Customers Will Think When You Offer a Data-Driven Customer Experience

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7 Things Customers Will Think When You Offer a Data-Driven Customer Experience

As a consumer, you know the scenario: You research a product online, purchase the item … and the next day you get an email or a retargeted digital ad from the same company, pitching you the exact same product you just bought.

This happens because the seller has some lag somewhere in their maze of marketing systems, and this results in annoyance for the customer and wasted ad dollars for the seller.

While every marketing department, whether B2B or B2C, yearns to earn the mantle of being a “data-driven” organization, challenges like this persist. Our earlier post What’s the Holdup with Data-Driven Marketing? looked at some of the other obstacles—but from the marketer’s perspective. 

How about flipping the camera around and looking at the same issue from the customer’s point of view? What might a full-blown, data-driven customer experience feel like for the buyer? 

True data-driven marketing must have the potential to do more than just help us avoid serving annoying, poorly targeted ads to customers, right? Three marketing experts say yes, and describe a North Star vision of how much more nuanced and valuable a data-driven customer experience can be. Applied well, data helps improve the customer experience from earliest contact—before any personalization can be applied—through the complex purchasing processes, and still further through customer service and retention.

Here’s what customers experience when data informs their interactions with your company:

1. “This company knows what information I like or need” 

Estimates vary wildly but it’s clear that the average person is subjected to hundreds or even thousands of marketing messages each day. Combine that with hundreds of texts and social media posts, and hours of streaming video, podcasts, web searches, and online content read for work or for leisure.

Even when buyers visit a website for a desired product or in search of information, they often have to weed through dozens of other things irrelevant to their specific interest at the moment —it’s a generic customer journey, with pages and messages prioritized based only on high-level data about what’s most popular, not specific to that customer.

Marketers search for the way to get a signal through all that noise by using methods such as “personalization” or by taking a “right message, right time, right place” approach. But on the rare occasions that the signal actually cuts through the noise, the customer is likely to think, “Finally, somebody who understands what I’m trying to do.”

Perhaps the best examples today are recommendation engines such as those used by Amazon.com to suggest  products or Netflix to suggest video content. At Amazon, for example, as much as half of the thousands of products sold each minute are purportedly served up via these recommendations, according to a recent Harvard Business Review article.

“Recommendation engines are the most powerful and invisible technology we have to work with,” says Christopher Penn, Chief Analytics Officer and co-founder at Trust Insights. “They’re determining the products you’re recommended, the things you’re told to watch on TikTok or Facebook.”

According to Penn, “Marketers of all stripes can adopt these tools to identify what is the next best content or email, even in the course of a complex B2B sales process.” In fact, it may be even more critical in such a context. “The more complex the sale, the more you need the right matching of offer to customer experience,” he says. 

While there are numerous SaaS options today for creating and training a recommendation engine, the first step is capturing enough meaningful data. Companies already working toward more precise customer segmentation are taking the right steps forward, says Lourenço Mello, Product Marketing Lead, Solutions, at Snowflake. Experimentation is helpful too, and classical marketing techniques such as A/B testing are part of the solution. (You are already A/B testing religiously, aren’t you?)

Customers who quickly get what they need from you will feel like your company “gets” them.

2. “They actually have the information I like or need”

Surveys find that more than 80% of companies say they use content marketing. Content marketing assets can do things straight-up ads typically don’t, particularly in transactions that require a good deal of research, education, and comparison.

However, even with the great volume of content available, much of it misses the mark.

Take technology purchasing, for example. A 2021 Customer Engagement Study of technology buyers, conducted by research firm Foundry, discovered that “only 41% of downloaded work-related content provided tech buyers with value over the past 12 months,” according to Stacey Rapp, Foundry’s Marketing and Research Manager.

Marketers who base their content on personas built with limited or superficial data (you know who you are) are likely to miss out on important details and have gaps in their content portfolio. Conversely, those companies that deliver marketing information of real value, whether short form or long, will stand out. 

You can’t deliver the right content at the right time if you haven’t created the right content in the first place. Digging deeper into data about customer behaviors can help ensure the right information is being created—web navigation and search data, certainly, but also extending to data about online communities, social interactions, and more. 

When marketers create valuable content and deliver it at the right time, Penn says the effect for customers is that they feel the company is “just slightly anticipating,” queueing up the correct information to help them with their next task.

3. “They understand the hoops I have to jump through” 

Speaking of tasks, buying isn’t simple. 

Even the B2C buyer’s journey has notoriously become more complex and less linear thanks to the proliferation of digital channels and social platforms. 

B2B purchases are fundamentally even more complex, and usually slower. For example, for technology products the purchase process lasts more than 6 months on average, according to another Foundry survey, Role & Influence of the Technology Decision-Maker 2022. And on average, as many as 20 employees “influence” this process—10 from the IT department and 10 additional line-of-business workers. 

Much B2B purchasing research is now conducted without direct input from the vendors. Gartner estimates that in tech, “any given sales rep has roughly 5% of a customer’s total purchase time” across the full buying cycle.

Every industry is its own animal, but similar complexity applies across B2B categories, whether it’s multimodal transportation services, biopharmaceutical manufacturing supplies, or global business insurance policies.

Marketing messages and information aren’t always aligned to help prospects deal with this complexity. The individual you’re communicating with may need a variety of tools to help inform their discussions with others on that buying committee. So a “data-driven” experience for this customer should be informed by rich, account-based information.

4. “They respect my privacy requirements”

According to 2022 research from BCG and Google, two-thirds of consumers want ads that match their interests, but only 31% describe themselves as “comfortable sharing their data” to create personalized ads. 

The numbers may vary as prospects move from advertisements toward purchasing, but privacy is a big concern, and only getting bigger. This can’t be forgotten in the rush to deliver a truly data-driven customer experience; in fact, it’s an inherent requirement.

“Marketers have really got to get sharp on developing their own data governance and control,” says Snowflake’s Mello. Otherwise, customer trust can be violated and hard to win back.

5. “They don’t waste my time”

Off-target ads are one issue, but companies can be perceived as wasting customers’ time in other ways as well.

Picture a B2B buyer who is researching a product category, finds a vendor’s helpful new research study, and wants to meet with that vendor. But they can’t schedule a meeting for two weeks, because since the study was released, the sales team has been swamped with requests. That’s two full weeks for a competitor to get in the buyer’s ear instead.

Couldn’t marketing data better inform the sales department about what to expect, or guide the study’s release in a more manageable way?

Guan Wang, Global Director of Marketing Intelligence for Snowflake, envisions a near future where these things are possible. “Instead of launching a campaign to a million people, marketers could interact with their database in real time based on profile, intent, as well as prior engagement, and build a real-time segment of maybe 20% of those people so they have a clear picture,” says Wang. “Before they send it out, they should be able to predict how many prospects they can engage, how many sales pipeline opportunities they will generate, what business outcomes they can drive.” 

Right now, this kind of work is usually more ad hoc or approximate, Wang says, but “that is the future of data-driven, predictive marketing.” This means the company is ready to engage whenever the customer is—no time wasted.

6. “They really do value my business”

If it’s true that it’s cheaper to keep a current customer than to land a new one, data-driven customer experience should extend throughout the lifecycle of the product or service, and on to renewal, recycling, or whatever comes next.

Trust Insights’ Penn says data science is becoming adept at spotting “if a customer is showing signs of going dormant. You can use things like Markov chains or neural networks to find those signals; the goal is to re-engage,” he says. 

This kind of customer care includes not only preventing imminent churn, but providing proactive customer service. Depending on their corporate structure, some marketers may argue that retention belongs to another department—and those pesky data silos rear their heads again. To deliver a seamless experience, data sharing across marketing, sales, post-sales support, and other departments is a must.

For the customer, all of this adds up to feeling valued.

7. “This company has its act together”

Think back to the opening example of serving a retargeted ad to someone who has already bought the product. Data latency of this type arises from data silos. 

Mello notes that the Martech Map has evolved from 150 marketing tools in 2011 to 9,932 in 2022. In years past, organizations accumulated a patchwork of tools and services, each performing a different function. Connecting the data from one system to another was often convoluted, even for companies that chose a single “marketing cloud” vendor with an allegedly integrated toolset—no single vendor provides all the functionality needed by every operation.

Even worse than the technology challenges, for some companies data silos reflect an organizational issue (such as a process- or metric-enforced divide between sales and marketing) or cultural issue (such as good, old-fashioned turf wars). 

Customer experience suffers when a company’s data is discombobulated. No amount of brand advertising or slick copywriting can overcome an individual’s frustration at not being able to find the right information and product.

Mello says there’s really no excuse to let silos undermine customer experience today. “We’re now at a point where marketers are understanding different tools in the modern marketing data stack,” he says. “They are able to pick best-of-breed partners for ingestion, modeling, analytics, business intelligence—we can pick and choose, and integrate seamlessly.” While the technology hurdles are falling, he says the bigger challenge now is in terms of skills. 

Regardless of what issues a given company has to overcome, Mello says the right way to arrive at data-driven marketing is to focus on business needs and start marching forward.

“The first step is to have a concrete business objective. We can’t jump straight to ‘let’s integrate all our data.’ The approach is to start with a business problem. Solve that. Then iterate.”

Experts agree it’s a journey that’s worth the effort. What better business need to examine than improving customer experience? The better you understand customers, the better your prospects and clients will feel. And the more likely you are to win and retain their business.

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