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Using AI to improve customer experience and customer journey orchestration

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Using AI to improve customer experience and customer journey orchestration

Customer-centric messaging and experiences require smart responses managed by AI. If customers aren’t receiving relevant emails or other communications, they’ll simply opt out.

“Right now, marketing is failing more than it works,” said Matthew Camuso, product marketing manager for CRM software company Pegasystems, at The MarTech Conference. “And if you think about why this fails, it’s because most of what we push, and when we push it, has no real relevance to the consumers.”

He cited an internal study of over 5,000 consumers that found that 68% of them don’t believe brands care about their needs.

If brands aren’t responding to customers’ needs intelligently with an AI tool, they are usually depending on prepackaged messages sent to clusters of customers, broken down into segments. The risk is that many customers within these segments will find the messaging irrelevant and get turned off to the brand.

Read next: Why we care about AI in marketing

Risks in traditional segmentation

In a traditional campaign, a customer base is divided by demographics, geographies and other categories to create segments, and even finer-tuned microsegments. Marketers can then add rules based on what is known about the customer, like their financial means or the interest they expressed on a particular webpage. Predetermined messages are then sent to this fixed group of customers.

“At the end of the day, you’re really just trying to find the best list of people that can buy your product, and then once you get that list, it’s a little smaller, but you target all those people across channels,” said Camuso.

This strategy generates a low percentage of sales, typically in the 1%-2% range, he said.

“That may hit your short-term campaign goals, which is great, but over the long term we’re so product-focused and sales-focused that it actually takes a toll on our customer relationships,” Camuso explained.

AI-driven customer-centric experiences

To drive customer-centric messaging and experiences, AI can be used to ingest customer signals from all channels, update the customer profile, and then propose next best actions that are relevant to those customers.

“What you need is a brain, a centralized decisioning authority, that can power all of your engagements and bring them together,” said Camuso. “What that brain will do is collect data about the customer from your channels, like email or web or mobile, and then combine that with historical data you have from a customer’s profile or interaction history, as well as anything that may be streamed in, in real time.”

Instead of a cookie-cutter campaign targeting a segmented list of customers, the communications managed and authorized by AI deliver personally relevant offers or suggestions.

Marketers also play a part in the AI decisioning by establishing criteria that are specific to their industry or product. For instance, if the brand is a bank, they can only sell a credit card to a customer that is 18 or older, and that rule should be added to the set of conditions for contacting a customer.

Within these narrower conditions, the AI can then arrive at next best actions, based on the desirability of the action to customer – designated in the algorithm as a “P” value (propensity) – and also based on the value (“V”) of the action or sale to the company.

Additionally, the AI will use internal business factors to reach its decision on the action. For instance, if a product has low inventory, the AI might determine that it’s better to put another product in front of the customer where there is higher inventory, so that the company can fulfill the sale.


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AI-driven customer journey orchestration

Every new piece of data that comes in about a customer triggers the AI to recalculate the score, keeping all messages current and relevant. A credit card purchase, for instance, could trigger a timely text, or even a helpful phone call from a live rep.

These message-based next best actions are an important part of the customer experience. But, the AI decisioning can also be used to build web pages and mobile experiences tailored to the customer based on the updated information in the customer’s profile.

Additionally, a customer-centric approach powered by AI can enable customer journey orchestration that is also more relevant and effective.

Traditional customer journeys are mapped out in straight lines using rules to push customers from one action or stage to the next. When a customer – any customer – does a specific action “X”, then they are moved forward in the process to another action, “Y,” based on the basic rules of the journey.

The difference with an AI-driven customer journey orchestration is that it can remain customer-centric and choose from a larger number of options that make sense to a specific customer based on the customer profile.

When the AI is guiding the journey, it can manage more complicated journeys that include many variables, which are all scored according to propensity. A good example for financial companies is a mortgage, which is a complicated process with a number of stages that are based on many personal data points.

“Ultimately it’s just trying to help customers achieve whatever they’re doing in that stage,” said Comuso. “And when they get to that step, we never try to force them to the next one. Instead, we look across all those journeys [from previous customers] and see where she is in the bigger picture, and then use real time decisioning and propensity modeling.”

Taking advantage of the scale provided by AI modeling, the goal is for every journey or message to be fresh and relevant to the current customer. If this goal is met, customers will have the impression that the brand really does care about their individual needs.

From ignored to engaged: Deliver better customer experiences with always-on marketing from Third Door Media on Vimeo.


About The Author

Chris Wood draws on over 15 years of reporting experience as a B2B editor and journalist. At DMN, he served as associate editor, offering original analysis on the evolving marketing tech landscape. He has interviewed leaders in tech and policy, from Canva CEO Melanie Perkins, to former Cisco CEO John Chambers, and Vivek Kundra, appointed by Barack Obama as the country’s first federal CIO. He is especially interested in how new technologies, including voice and blockchain, are disrupting the marketing world as we know it. In 2019, he moderated a panel on “innovation theater” at Fintech Inn, in Vilnius. In addition to his marketing-focused reporting in industry trades like Robotics Trends, Modern Brewery Age and AdNation News, Wood has also written for KIRKUS, and contributes fiction, criticism and poetry to several leading book blogs. He studied English at Fairfield University, and was born in Springfield, Massachusetts. He lives in New York.

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Take back your ROI by owning your data

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Treasure Data 800x450

Treasure Data 800x450

Other brands can copy your style, tone and strategy — but they can’t copy your data.

Your data is your competitive advantage in an environment where enterprises are working to grab market share by designing can’t-miss, always-on customer experiences. Your marketing tech stack enables those experiences. 

Join ActionIQ and Snowplow to learn the value of composing your stack – decoupling the data collection and activation layers to drive more intelligent targeting.

Register and attend “Maximizing Marketing ROI With a Composable Stack: Separating Reality from Fallacy,” presented by Snowplow and ActionIQ.


Click here to view more MarTech webinars.


About the author

Cynthia RamsaranCynthia Ramsaran

Cynthia Ramsaran is director of custom content at Third Door Media, publishers of Search Engine Land and MarTech. A multi-channel storyteller with over two decades of editorial/content marketing experience, Cynthia’s expertise spans the marketing, technology, finance, manufacturing and gaming industries. She was a writer/producer for CNBC.com and produced thought leadership for KPMG. Cynthia hails from Queens, NY and earned her Bachelor’s and MBA from St. John’s University.

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Revolutionizing Auto Retail: The Game-Changing Partnership Between Amazon and Hyundai

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Revolutionizing Auto Retail: The Game-Changing Partnership Between Amazon and Hyundai

Revolutionizing Auto Retail The Game Changing Partnership Between Amazon and Hyundai

In a groundbreaking alliance, Amazon and Hyundai have joined forces to reshape the automotive landscape, promising a revolutionary shift in how we buy, drive, and experience cars.

Imagine browsing for your dream car on Amazon, with the option to seamlessly purchase, pick up, or have it delivered—all within the familiar confines of the world’s largest online marketplace. Buckle up as we explore the potential impact of this monumental partnership and the transformation it heralds for the future of auto retail.

Driving Change Through Amazon’s Auto Revolution

Consider “Josh”, a tech-savvy professional with an affinity for efficiency. Faced with the tedious process of purchasing a new car, he stumbled upon Amazon’s automotive section. Intrigued by the prospect of a one-stop shopping experience, Josh decided to explore the Amazon-Hyundai collaboration.

The result?

A hassle-free online car purchase, personalized to his preferences, and delivered to his doorstep. Josh’s story is just a glimpse into the real-world impact of this game-changing partnership.

Bridging the Gap Between Convenience and Complexity

Traditional car buying is often marred by complexities, from navigating dealership lots to negotiating prices. The disconnect between the convenience consumers seek and the cumbersome process they endure has long been a pain point in the automotive industry. The need for a streamlined, customer-centric solution has never been more pressing.

1701235578 44 Revolutionizing Auto Retail The Game Changing Partnership Between Amazon and Hyundai1701235578 44 Revolutionizing Auto Retail The Game Changing Partnership Between Amazon and Hyundai

Ecommerce Partnership Reshaping Auto Retail Dynamics

Enter Amazon and Hyundai’s new strategic partnership coming in 2024—an innovative solution poised to redefine the car-buying experience. The trio of key developments—Amazon becoming a virtual showroom, Hyundai embracing AWS for a digital makeover, and the integration of Alexa into next-gen vehicles—addresses the pain points with a holistic approach.

In 2024, auto dealers for the first time will be able to sell vehicles in Amazon’s U.S. store, and Hyundai will be the first brand available for customers to purchase.

Amazon and Hyundai launch a broad, strategic partnership—including vehicle sales on Amazon.com in 2024 – Amazon Staff

This collaboration promises not just a transaction but a transformation in the way customers interact with, purchase, and engage with their vehicles.

Pedal to the Metal

Seamless Online Purchase:

  • Complete the entire transaction within the trusted Amazon platform.
  • Utilize familiar payment and financing options.
  • Opt for convenient pick-up or doorstep delivery.
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Hyundai’s Cloud-First Transformation:

  • Experience a data-driven organization powered by AWS.
  • Benefit from enhanced production optimization, cost reduction, and improved security.

Alexa Integration in Next-Gen Vehicles:

  • Enjoy a hands-free, voice-controlled experience in Hyundai vehicles.
  • Access music, podcasts, reminders, and smart home controls effortlessly.
  • Stay connected with up-to-date traffic and weather information.

Driving into the Future

The Amazon-Hyundai collaboration is not just a partnership; it’s a revolution in motion. As we witness the fusion of e-commerce giant Amazon with automotive prowess of Hyundai, the potential impact on customer behavior is staggering.

The age-old challenges of car buying are met with a forward-thinking, customer-centric solution, paving the way for a new era in auto retail. From the comfort of your home to the driver’s seat, this partnership is set to redefine every step of the journey, promising a future where buying a car is as easy as ordering a package online.

Embrace the change, and witness the evolution of auto retail unfold before your eyes.


Revolutionizing Auto Retail The Game Changing Partnership Between Amazon and Hyundai

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How to Schedule Ad Customizers for Google RSAs [2024]

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How to Schedule Ad Customizers for Google RSAs [2024]

It’s no wonder that responsive search ads have steadily grown in popularity in recent years. Through Google’s machine learning capabilities, RSAs provide a powerful way to automate the testing of multiple headlines and descriptions to ensure a closer match to user intent. The benefits are clear: RSAs mean broader reach, better engagement, and improved performance metrics.

However, all these benefits come at a significant (but reasonable) cost – they can be extremely difficult to manage, especially when it comes to updating ad copy to promote limited time offers.

I know this firsthand – I work with several ecommerce clients with promotions that constantly change. Not too long ago, I found myself going through the consistently tedious process of updating a client’s RSA headlines and copy. As I was making the changes, I thought to myself: “There must be a better way to update this ad copy. I shouldn’t have to use find and replace so many times while pausing and enabling my ad campaigns.”

After expressing this to my colleague, Jordan Stambaugh, the two of us agreed there must be a better way. But we’d have to make it happen. A few weeks later, we put that idea into action and created a more efficient process for updating RSA ad copy on a scheduled basis. If you want to try this process for yourself, just keep reading.

Responsive Search Ad Customizers 101: Basic Options & Execution

Before diving into the process of scheduling automatic updates for your RSA customizers, it’s essential to understand some key Responsive Search Ad fundamentals.

First, you can customize three main options within RSAs: the Attribute Name, the Data Type, and the Account Value. Each of these plays a vital role in personalizing your ads:

  • Attribute Name: This is essentially the identifier for the customizer. It is how you’ll reference the specific piece of information you’re customizing within the ad. For instance, if you’re running a promotion, you might name an attribute “Promotion.”
  • Data Type: This indicates the kind of data the attribute represents and it determines how the information can be formatted and used within the ad. Common data types include Text (for plain, non-numeric text), Percent (to represent percentage discounts), Price (to denote monetary values), and Number (for any numerical value).
  • Account Value: This is the default value for the attribute that you set at the account level. It acts as a fallback if more specific values aren’t provided at the campaign or ad group level.

For example, if you wanted to promote a 10% off discount using RSAs, you’d use the “Discount” attribute, a data type of “Percent,” and an account value of “10% off.” Then, when someone is searching for products, Google would test automatically inserting a copy regarding a 10% off promotion into your ad.

Once you’ve set up the right customization options, you can start to format your RSAs with customizers.

Here’s how:

  • Start by typing in {
  • Click on Ad Customizer then select your attribute
  • Google will populate your attributes that are already uploaded
  • For a simple offer, use the “Default text” attribute as a catch-all. This will ensure your ads run smoothly if Google can’t pull the right messaging from your RSA feed

 

 

How to Schedule Your Ad Customizers with a Feed

Now that we’ve covered the basics, let’s cover how to schedule your ad customizers.

Just follow this three step process:

1. Create the feed

Start by creating two sheets: The Parent sheet, and the Child sheet. The “Parent” sheet will act as the primary data source, while the child sheet will pull data from the parent sheet.

We’ll start by building the parent sheet. After opening the sheet, start by renaming the active tab to “Promotions.” Don’t skip this step, it’s crucial for referencing this range in formulas later on.

In your “Promotions” tab, head to the top row and label columns A, B, and C with the headers of your ad customizer attributes. For example, you might have “BrandSaleHeadline” as your attribute in column A, “text” as the Data Type in column B, and “Shop the Collection” as the Account Value in column C.

Once your headers are in place, move to cell C2. Here, you’ll input the expression =lookup(today(),F:G,E:E). This formula will play a key role in dynamically updating your RSA customizer based on the current date.

Next, go to columns E, F, and G, which will be used to manage your scheduling. In these columns, you’ll list out the different values your chosen attribute might take, alongside their corresponding start and end dates. For example, under the “BrandSaleHeadline” attribute, you might schedule various promotional headlines to appear during different sale periods throughout the year.

Here’s how your sheet might look:

Now look back at the first 3 columns on your sheet. They should look like this:

Now create a second sheet. We’ll call this sheet the Child sheet. It’s going to automatically pull in data from the parent sheet you just created, and will be the one you link to Google Ads later on.

Columns A, B and C will be almost identical to the child sheet, but we will be using a special formula later so we can automatically populate this. So, start by labeling Row 1 Column A “Attribute,” then the next column as “Data type,” then column C as “Account value.” 

Then go to C2 and use this expression to populate the right account value from the parent document: =importrange(“[PARENT DOCUMENT URL HERE]”,”Promotions!C2″)

Your sheet should now look like this:

We recommend adding a date range with default text for any days you’re  not running a promotion. In the example above, we have “Shop Our Collection” appearing as default text.

2. Input attributes

Once you have your feed created, the next step involves inputting your attributes into the Google Ads platform. This can be done either manually or through a bulk upload.

For the manual approach, navigate to “Tools & Settings” in your Google Ads interface, then go to ‘Setup’ followed by “Business Data.” Here, you’ll find an option for “Ad Customizer Attributes.” Click the plus sign to add your attributes. It’s crucial to use the same attribute names that you’ve established in your Parent Google Sheet template to ensure consistency and proper data synchronization.

 

 

Alternatively, if you prefer the bulk upload method, again head to “Tools & Settings.” This time, select “Bulk Actions” and then “Uploads.” For this process, you only need to upload columns A to C from your template. 

Be aware that it might take some time for your uploaded attributes to be reflected in the business data section of Google Ads.

3. Set up an automatic schedule

At this point, you’ve almost finished scheduling your ad customizers. Navigate to Tools & Settings, then Bulk Actions, then Uploads, then click the Schedules tab at the top. Select your Child Google Sheet as the data source, and share your Google Sheet with the appropriate email.

 

 

And there you have it – Google will automatically pull in the data you populated in the sheets into your RSAs.

Common Challenges When Scheduling RSA Ad Customizers

When we test these sheets with our clients in the wild, we’ve uncovered five common challenges. Be on the lookout for these issues – solving them before they happen can save you a lot of trouble down the line.

Not scheduling your upload when the site changes 

The first and most significant hurdle is the mismatch between the scheduled data upload and website content updates. For instance, if the Google Sheet is set to upload at 11 am, but the website changes occur at 3 pm, there’s going to be a discrepancy where the wrong message could be displayed for several hours, or new messaging could appear prematurely. Conversely, if the website updates happen before the scheduled sheet upload, outdated promotions might linger until the new data is imported. Synchronizing these schedules is crucial; it’s best to align them so updates occur simultaneously.

Skipping QA during a message change

Another pitfall is neglecting quality assurance (QA) during message updates. It’s vital to regularly check the business data section to verify that the correct values are in place post-update.

Issues with the IMPORTRANGE function

Then there’s the technical aspect of setting up the IMPORTRANGE function correctly in the Google Sheets template. The ‘child’ template must reliably pull data from the ‘parent’ sheet. If this function isn’t configured correctly, data won’t be imported as needed.

Not sharing access of the Google template for automatic uploads

Pay attention to your access permissions for the Google Sheets template. Google will prompt you with the email address that needs permission to access the ‘child’ sheet for automatic uploads. Overlooking the sharing of your sheet with this address will prevent the system from working.

Having date range gaps in your parent sheet

Lastly, a common oversight is leaving date range gaps in the ‘parent’ sheet. Every single date must be accounted for without overlaps. A practical tip is to have an ‘evergreen’ backup message ready, scheduled to run continuously, ideally through the end of the year, to cover any potential gaps.

Conclusion

Leveraging Google Sheets in conjunction with Google Ads to schedule RSA ad customizers is a game-changer for managing dynamic promotional content. This process not only streamlines your workflows but also ensures that your ads remain relevant and up-to-date, reflecting current promotions without the need for constant manual intervention. 

By adopting this method, you’ll save significant time and effort, allowing you to focus more on strategy and less on the minutiae of ad copy updates. Give it a try and experience a more efficient way to manage your RSAs, keeping your campaigns fresh and engaging with minimal hassle.

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