{"id":6001,"date":"2023-12-28T17:05:53","date_gmt":"2023-12-28T17:05:53","guid":{"rendered":"https:\/\/tup.kxe.temporary.site\/how-ais-describe-and-done-can-revolutionize-your-work\/"},"modified":"2023-12-28T17:05:53","modified_gmt":"2023-12-28T17:05:53","slug":"how-ais-describe-and-done-can-revolutionize-your-work","status":"publish","type":"post","link":"https:\/\/okdesign.ca\/fr\/how-ais-describe-and-done-can-revolutionize-your-work\/","title":{"rendered":"How AI’s ‘describe and done’ can revolutionize your work"},"content":{"rendered":"


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In their \u201cMartech for 2024\u201d report<\/a>, Scott Brinker and Frans Riemersma compared AI\u2019s adoption to a compressed version of Gartner\u2019s Hype Cycle<\/a>. Certainly, the pace of change in martech now is unprecedented.<\/p>\n

We see this in the rate at which martech vendors released beta features to users over the past year. Many of those features were infusions of AI into existing applications. We are clearly in the midst of an \u201cAI arms race,\u201d triggered by the release of ChatGPT just over a year ago.\u00a0<\/p>\n

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In my previous three pieces for MarTech, I focused on the overall trends<\/a>, data quality<\/a> and content\/campaign governance<\/a>. Each of those areas is being impacted by the incredible pace of change brought about by AI.\u00a0<\/p>\n

Dig deeper: <\/em><\/strong>3 ways email marketers should actually use AI<\/em><\/strong><\/a><\/p>\n

This piece focuses on the integration capabilities in customer relationship management (CRM) and marketing automation platforms (MAPs). These integrations typically involve data management capabilities.\u00a0\u00a0<\/p>\n

To explore this, we\u2019ll walk through a hands-on test with Zapier, one of the leading workflow platforms. As we walk through the test, you\u2019ll see how Zapier is infusing AI capabilities in its beta releases.<\/p>\n

Hands-on test: Integrating online shopper data<\/h2>\n

My hands-on test was conducted with the following fictional use case:<\/p>\n

The shopping system of record for a home-grown business is its proprietary, legacy ecommerce tool. To accommodate growth, the business plans to deploy a CRM\/MAP for customer marketing and customer service outreach.<\/em><\/p>\n

In this scenario, the legacy system only outputs data in the .csv format through a conversion spreadsheet (in Google Sheets) because it was previously determined that building a full database interface would tax the available resources.<\/p>\n

Next, I set up a sample set of consumer ecommerce shopping data. The consumer profiles were generated by ChatGPT.<\/p>\n

\"FIg4Kpzu\"FIg4Kpzu<\/figure>\n
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\"2024\"2024<\/figure>\n
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Take Martech\u2019s 2024 Salary and Career Survey<\/h3>\n

From AI to layoffs, it\u2019s been quite a year. We\u2019d like to know how it\u2019s been for you. Please take this short survey so we can have your input on the state of martech salaries and careers.<\/p>\n

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\u2018Point-and-click\u2019 gives way to \u2018describe-and-done\u2019<\/h2>\n

Zapier is a popular platform often used for integrations like the one I\u2019m simulating here. The beta release of Zapier\u2019s Zap builder uses prompts and AI to guide users through the process of building an integration.\u00a0<\/p>\n

Here is the starting prompt:<\/p>\n

\"NqL7aVoVb5PUo2GPG6sy5O\"NqL7aVoVb5PUo2GPG6sy5O<\/figure>\n

My initial, generic prompt helped the system focus on \u201cHubSpot\u201d as a keyword. However, the system helpfully informed me it needed more information to create a complete workflow.<\/p>\n

\"28uzz\"28uzz<\/figure>\n

My revised prompt included the Google Sheets language:<\/p>\n

\"BszJ94qPO7z6UAfoCc54bCjfKvqWDF9sfY\"BszJ94qPO7z6UAfoCc54bCjfKvqWDF9sfY<\/figure>\n

While this is still a relatively simple example, the Zap results signaled a more powerful future. The implications of using natural-language AI prompts to build full technical interfaces are far-reaching. This extends beyond \u201cno-code.\u201d It\u2019s a game changer for basic users of technology.<\/p>\n

This is an example of a broader trend addressed by HubSpot co-founder Dharmesh Shah when HubSpot released its ChatSpot AI capabilities<\/a> in March 2023. He said we\u2019re shifting from \u201cpoint-and-click to describe-and-done\u201d<\/a> in a more natural, declarative approach. In other words, AI is helping software vendors create more human-friendly interfaces.<\/p>\n

AI structures the unformatted and unstructured data<\/h2>\n

In the real world, it\u2019s entirely possible the legacy data in our test would be delivered in unformatted and unstructured formats. Therefore, my next step was to consider a data formatting Zap.<\/p>\n

Once again, I created a prompt, this time to help me format the Average Purchase Value as U.S. dollars.<\/p>\n

\"M5Ua28N4PQmdYI3RpEvlQRbsEAqUf5Jm47mJLv995pYusB9\"M5Ua28N4PQmdYI3RpEvlQRbsEAqUf5Jm47mJLv995pYusB9<\/figure>\n

Here\u2019s a similar scenario. Let\u2019s assume that the legacy system stored customer service comments with lots of unnecessary formatting (e.g., various uncommon delimiters). This would typically require coding and or formatting to extract value from the data.\u00a0<\/p>\n

I explored Zapier\u2019s capability to produce that code for me. The following was the resulting Zap, created with Zapier\u2019s AI-assisted Python coding capability.<\/p>\n

\"Ce5uJO9J5wIOtZqJmyMx0NIP80kymAYyBocIrT7wH7ClwMBnBQQnUMrKED6ATySN4Vw9D3LImFpnHicGe6zgJUaAI8hmpAkYRM1KRFgaacU2MlCafHAxYTuYdPsacgHwlfSjRtHdHp5R3Fdc7w1mst0\"\"Ce5uJO9J5wIOtZqJmyMx0NIP80kymAYyBocIrT7wH7ClwMBnBQQnUMrKED6ATySN4Vw9D3LImFpnHicGe6zgJUaAI8hmpAkYRM1KRFgaacU2MlCafHAxYTuYdPsacgHwlfSjRtHdHp5R3Fdc7w1mst0\"\/<\/figure>\n
\"IgXZ4kOhfuTO\"IgXZ4kOhfuTO<\/figure>\n
\"8BnRXYd\"8BnRXYd<\/figure>\n

Conclusions<\/h2>\n

I used natural language prompts and Zapier\u2019s AI capabilities to create an integration between a legacy, proprietary ecommerce system, Google Sheets and HubSpot. Then I created Python code to format data fields to extract value from unstructured data.<\/p>\n

What did I learn from this test? What will I take into 2024?<\/p>\n