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State of Grace: The Future of Data-Driven Marketing

For a long time, advertisers have had a dirty data secret. Data protection has become the interest of both governments and consumers, and brands are at risk of losing out on the third-party data they’ve long relied on. Data-driven marketing has been one of the most disruptive ways businesses have grown in the last two decades, but now only 45% of consumers now trust organizations to protect the privacy of their personal data, and 44% have taken steps to reduce the amount of data they share online.

In this post-GDPR world, marketing choices of the past don’t just come home to roost with regulators. They also elicit the hesitance and privacy concerns of data-savvier consumers, who are starting to think twice about the way they interact with brands and advertisers, and also make first-party data more essential than ever before for brands.

While developing first-party data is critical, brands also need a methodology to overcome the data-driven marketing “sins” of the past. Those in a state of “grace” – who use new methodology to avoid the sins of the past – have the opportunity to get through to jaded consumers, drive meaningful engagements, and leverage even better data than ever before.

Why Should Data-Driven Marketing Seek Redemption?

In theology, the concept of grace evokes those who are without sin, heavenly or otherwise. For marketers, we may not think of ourselves as sinful, but we are like others sinners in that we commit transgressions we don’t always admit to. This could be emails to non-subscribed lists, ad content or audience targeting that is ethically questionable, or simply marketing products and services that we neither truly believe in nor may actually be good for their consumers.

For marketers at major brands, there are in fact ”Seven Deadly Sins of Advertising” that have come to undermine trust and make it difficult for brands to succeed. 69% of consumers no longer trust advertising, and Advertising Association President Keith Weed defines the causes of this as follows:

  • Declining quality of advertising on television and elsewhere
  • Inauthentic activity by fake followers and likes on social media
  • Concerns over personal data and its likelihood to be exploited
  • Advertising funding bad actors, extremism and unsafe media
  • Greater appearance of fake news, which has reduced trust in advertising by 35% alone
  • Annoying personalization, which a plurality of consumers find irrelevant to their needs
  • Excess of ads, which Weed says now exceeds 10,000 brand messages per day for each consumer

To simplify this set of problems into the true crisis from which marketers need redemption:

There are too many bad ads using my stolen data and fake engagement to help bad people promote false information that doesn’t matter to me anyway.

There are plenty of ways to put these problems together, but it seems that advertising and our use of data is fundamentally broken, and we need a new paradigm to change our approach to messaging with and generating data on consumers. 

What is Grace for Data-Driven Marketing?

Grace is simple, but powerful. Guidance, Recommendation, Advice, Consultation and Expertise (or GRACE, in the tradition of capitalized acronyms) are all practices which we are used to in teaching, informing and selling. Where marketers apply them, they can increase engagement, insight and revenue.

With the right technology, they can also create a more intimate, connected experience for consumers. This can lead to better results than traditional data-driven marketing, while also making the consumer more likely to see that brand as informative, fun, friendly, easy and helpful. Conversational AI allows for this by starting a conversation with consumers – in a one-to-one, automated, scalable way – and thus stands apart from traditional one-way ads, emails and more, no matter how personalized they are.

Grace is a compelling model for brand marketers to use, but before you use it, you have to understand what it is and learn to see the opportunities to use it. The most straightforward way to talk about these concepts is as follows:

“I use Guidance to help consumers find the right products and solutions for them.”

“I use Recommendations to make it easier for consumers to discover their best choices.”

“I use Advice to build trust without aggressively pushing consumers to a final decision.”

“I use Consultation to offer proof of results before asking for commitment.”

“I use Expertise to help consumers understand the product inside and out, and be sure it’s the right choice for them”

This framework could be thus applied to any given scenario where marketers attempt to condition an experience and drive a consumer to purchase, and do so in a more transparent, direct way that relies on data they declare themselves. 

What’s important to consider, however, is that you aren’t limited to using conversational experiences in a grace framework and enhance your data-driven marketing. If you know a consumer has an affinity group, or identifies particular concerns on a form or other communication or conversion with your brand, you don’t just need to send them a discount code.

Use content, trial experiences, related products, tutorials, or drive the consumer to a nearby retail store – any one of these value-adds can provide grace and further the metaphorical “conversation” you’re having with your consumer. This drives greater insight, because as consumers interact, they teach you what they’re looking for. If you can drive them in more subtle ways to convert, you’re also more likely to do it in the future, and increase their lifetime value as a result.

With this kind of methodology, marketers and advertisers can reinvent the way they engage consumers and overcome the trust challenges they face today. They can also begin to develop their own first-party data that consumers have willingly agreed to share, and feel a benefit from sharing because it gives greater context and value to the recommendations and other assistance that a brand offers them. As one Salesforce study shows, 83% of consumers are willing to enable a personalized experience – as long as that experience is of sufficient quality, it shows trust isn’t totally dead.

How Guidance, Recommendation and Responses Support Data-Driven Marketing

The motivation for using a “grace” framework is clear, but the execution can be tricky. This is where Conversational AI makes it easier to apply to data-driven marketing efforts, and do so in real time.

Conversational AI is chatbots, voice assistants, any machine that you can talk to, and more and more brands are using it to increase engagement, insight and sale. By engaging users in conversational experiences, Conversational AI adds value for the consumer over traditional forms of marketing and advertising, surfacing needs, identities and relevant concerns and then reflexively offering the guidance, recommendations and personalized responses that better impel consumers to convert.

The knock-on benefit – and why this first-party data is the future of data-driven marketing and data protection – is that every one of these data points can be stored in a CRM and used in the future, whether in deepening a conversational relationship or better personalizing any offers, promotions, sales and seasonal campaigns.

As seen in the example below, when a user is engaged with a virtual skincare advisor, they can opt into personalized diagnostics that lead to product recommendations. The insights and customer data collected here are easily stored to a CRM, and gives a brand the resources to then engage in the future.

As the experience progresses, a variety of informative content and resources help demonstrate expertise and build trust with the user, deepening the relationship and allowing for further collect data in a consent-driven way.

Once the experience offers a recommendation, the consumer can actually engage in a purchase interface, gracefully transitioning them to a sale without any of the creepy or irrelevant personalization that many marketing practices are known for. With Conversational AI in tow, a brand is uniquely positioned to overcome the challenges of the modern advertising landscape, and uniquely deploy new data-driven marketing strategies that will achieve results in the coming years.

Making Data-Driven Marketing a “First-Party” Party!

Consumers and regulators are both suspicious of how brands get data and how they use it to drive business. With more privacy efforts coming from the likes of Google and Facebook, brands need to develop their own sources of data and do so in a compliant, opt-in way. Done the right way, brands don’t just have the opportunity to maintain the benefits of their data-driven marketing efforts – they can improve upon them in personalized and relevant ways never before possible.

Data-driven marketing has been a blessing in so many ways, but as consumer use of technology matures, we need to adopt new wrinkles and nuances to our approach to stay at the cutting edge. Leveraging traditional user profile information and context-driven advertising systems has been a great boon for brands of all stripes, but brands need to build on those benefits to keep getting great results into the future. “Grace” won’t be the only way to maintain a data-driven marketing approach, but at the very least, it will be the most elegant.

Still have questions?  We’re fired up to help as many brands as possible to raise the bar of user and customer experience in eCommerce.  If you need help implementing website engagement tools for your brand or want to talk further about any of the tactics in this article, we should talk ASAP!

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