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What is User Story Mapping? Steps, Examples + Best Tools Available

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What is User Story Mapping? Steps, Examples + Best Tools Available

Picture this: You’re a product owner and your team has a backlog of features to implement.

The problem is: Your team is overwhelmed and no one is sure where to start and how to prioritize the tasks. Well, this is where user story mapping can come in handy.

Keep reading to learn how user story mapping is helping product teams get a better understanding of consumer needs and prioritize tasks with a user-first approach.

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Before we get into user story mapping, let’s go over the basics. A user story is a short and simple description of a feature told from the perspective of the user. For example, “As a user, I can add items that I’m not ready to purchase yet to my wishlist.”

It forces product teams to build with a user-first approach. A user story map takes this a step further by visualizing the steps a user takes to complete an action.

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When product managers, designers, and developers work on a product, sometimes they focus too much on feature specifications. User story mapping gets them out of this framework and redirects them to focus on consumer needs and desired outcomes.

In addition, a user story map will help break down the customer journey into bite-size pieces that teams can tackle and ensure nothing gets lost in the process.

But to be clear, the mapping process isn’t solely for product teams. It can be a valuable cross-functional exercise that helps align marketing, engineering, UX/Design teams along with other departments.

In addition to getting everyone on the same page, creating a user story map also helps:

  • Determine how to prioritize work if there’s a large backlog of feature implementations, separating must-haves from nice-to-haves.
  • Break down requirements and visualize how each piece interacts with the other.
  • Expose roadblocks and dependencies that can impact product delivery.

Is agile story mapping different?

The short answer is no because user story mapping is used within an agile framework.

User stories are used in an agile framework as a way to provide context using simple and natural language. They also represent the smallest unit of work, just as sprints and epics are other measurements.

So, it’s agile story mapping is another way to describe the process of mapping a user story.

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User story mapping typically happens at the beginning of a project, as it helps offer structure and get everyone on the same page. However, it can be used at any phase of the project to help identify roadblocks and reprioritize.

  1. Set the frame.

Before you start mapping the story, you’ll want to narrow the scope. Otherwise, you may quickly start feeling overwhelmed and unable to start.

Here are some questions you should be asking:

  • What problem are we trying to solve?
  • How does this feature add value?
  • Who is the audience subset we are building for? (If any)

Once you answer these questions, put it in user story format: “As a [user], I want to be able to [filter my search] results so that I can [quickly find what I’m looking for.”

Following this approach will help you approach the problem tactically.

2. Map out the activities and the steps in the story.

In this step, you want to create a general roadmap for how the user would access and use this feature. Those are your main activities.

The goal here is to outline the big steps necessary to get from start to finish. From there, you lay out the steps.

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Following the same example from the previous section, here’s how it could look:

Activities:

  • Search for products.
  • Review product details.
  • Check out. 

Steps:

  1. Type into the search bar and head to the results page.
  2. Scroll through search results in search of specific information.
  3. Select the filtering option to narrow down options by cost.
  4. Review the search results page again with updated options.
  5. Select item and place in cart.
  6. Complete purchase.

As you’ll notice, story mapping requires going from macro to micro.

You’ll likely use input from your participants to map out these details. You want your map to paint an accurate and full picture of what does (and can) happen in this story.

So, you’ll want to lean on your team for input in this step.

3. Group and define the tasks.

Once you’ve mapped out the big details, this is where the collaboration takes off.

Under each step, you should highlight the key actions involved in each activity.

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For instance, when a user is in step 5, which is selecting an item and placing it in their cart, there are several substeps they will follow, including viewing the image, reading reviews, scanning related items.

All of these should be mentioned under the big activity groups, also known as the steps. The goal is to identify any gaps in the features of your product currently.

By adding a must-have, could-have, and should-have options in your map, you can rank features by priority. Here’s what you want to consider:

  • Is there anything else your user could do during one of these activities?
  • What could disrupt their process at this point? Where could they get stuck?
  • How else could the user navigate through this page?

This will require a collective effort from your various teams to figure out what’s realistic and what’s doable. For instance, an engineer might point out that a particular task is too big to count as one iteration. Your user researcher could highlight an important step in the process that you guys hadn’t considered.

4. Slice your tasks and get your minimum viable product.

Once everything is laid out, you and your team can start to move through the map to prioritize a list of tasks and cut them into slices.

Each “slice” will include tasks from each activity to create a viable end-to-end experience. It should have a clear outcome as well as a way to measure success. This will be important later when testing and tracking user behavior.

You will continue to separate your slices until you include all the tasks and have a clear plan to move forward.

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User Story Mapping Example

In this example, the user story is as follows: “As a user, I want to buy a product easily on this website.”

Once you have all those details, then you can create your map.

user story mapping example

Once you’ve added the activities, steps, and tasks, now you can figure out your slices. 

user story mapping example

For instance, in this example, the first slice would skip two tasks in the “Search” activity, skip three in the “Get product details” one, and three in the “Check out” section.

The second slice would include features like “Search by category” and “See product in AR.” Once you have all your slices, your team is ready to get to work. 

User Story Mapping Tools

When it comes to user story mapping, there are a lot of ways you could do this.

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The most straightforward way is with a conference room, a whiteboard, and a whole lot of sticky notes. That way, you can easily move pieces around as you work and make it a collaborative effort.

Now, if your team is remote, you’ll have to rely on online tools to assist you in this process. Many agile project management software have story mapping features, such as Atlassian’s Jira.

Additional online tools for user story mapping include Featmap, Miro, and Avion.

If your product team can’t agree on where to start for an upcoming or ongoing project, consider creating a user story map. It may take some time away from building but it will definitely pay off down the line.

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YouTube Ad Specs, Sizes, and Examples [2024 Update]

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YouTube Ad Specs, Sizes, and Examples

Introduction

With billions of users each month, YouTube is the world’s second largest search engine and top website for video content. This makes it a great place for advertising. To succeed, advertisers need to follow the correct YouTube ad specifications. These rules help your ad reach more viewers, increasing the chance of gaining new customers and boosting brand awareness.

Types of YouTube Ads

Video Ads

  • Description: These play before, during, or after a YouTube video on computers or mobile devices.
  • Types:
    • In-stream ads: Can be skippable or non-skippable.
    • Bumper ads: Non-skippable, short ads that play before, during, or after a video.

Display Ads

  • Description: These appear in different spots on YouTube and usually use text or static images.
  • Note: YouTube does not support display image ads directly on its app, but these can be targeted to YouTube.com through Google Display Network (GDN).

Companion Banners

  • Description: Appears to the right of the YouTube player on desktop.
  • Requirement: Must be purchased alongside In-stream ads, Bumper ads, or In-feed ads.

In-feed Ads

  • Description: Resemble videos with images, headlines, and text. They link to a public or unlisted YouTube video.

Outstream Ads

  • Description: Mobile-only video ads that play outside of YouTube, on websites and apps within the Google video partner network.

Masthead Ads

  • Description: Premium, high-visibility banner ads displayed at the top of the YouTube homepage for both desktop and mobile users.

YouTube Ad Specs by Type

Skippable In-stream Video Ads

  • Placement: Before, during, or after a YouTube video.
  • Resolution:
    • Horizontal: 1920 x 1080px
    • Vertical: 1080 x 1920px
    • Square: 1080 x 1080px
  • Aspect Ratio:
    • Horizontal: 16:9
    • Vertical: 9:16
    • Square: 1:1
  • Length:
    • Awareness: 15-20 seconds
    • Consideration: 2-3 minutes
    • Action: 15-20 seconds

Non-skippable In-stream Video Ads

  • Description: Must be watched completely before the main video.
  • Length: 15 seconds (or 20 seconds in certain markets).
  • Resolution:
    • Horizontal: 1920 x 1080px
    • Vertical: 1080 x 1920px
    • Square: 1080 x 1080px
  • Aspect Ratio:
    • Horizontal: 16:9
    • Vertical: 9:16
    • Square: 1:1

Bumper Ads

  • Length: Maximum 6 seconds.
  • File Format: MP4, Quicktime, AVI, ASF, Windows Media, or MPEG.
  • Resolution:
    • Horizontal: 640 x 360px
    • Vertical: 480 x 360px

In-feed Ads

  • Description: Show alongside YouTube content, like search results or the Home feed.
  • Resolution:
    • Horizontal: 1920 x 1080px
    • Vertical: 1080 x 1920px
    • Square: 1080 x 1080px
  • Aspect Ratio:
    • Horizontal: 16:9
    • Square: 1:1
  • Length:
    • Awareness: 15-20 seconds
    • Consideration: 2-3 minutes
  • Headline/Description:
    • Headline: Up to 2 lines, 40 characters per line
    • Description: Up to 2 lines, 35 characters per line

Display Ads

  • Description: Static images or animated media that appear on YouTube next to video suggestions, in search results, or on the homepage.
  • Image Size: 300×60 pixels.
  • File Type: GIF, JPG, PNG.
  • File Size: Max 150KB.
  • Max Animation Length: 30 seconds.

Outstream Ads

  • Description: Mobile-only video ads that appear on websites and apps within the Google video partner network, not on YouTube itself.
  • Logo Specs:
    • Square: 1:1 (200 x 200px).
    • File Type: JPG, GIF, PNG.
    • Max Size: 200KB.

Masthead Ads

  • Description: High-visibility ads at the top of the YouTube homepage.
  • Resolution: 1920 x 1080 or higher.
  • File Type: JPG or PNG (without transparency).

Conclusion

YouTube offers a variety of ad formats to reach audiences effectively in 2024. Whether you want to build brand awareness, drive conversions, or target specific demographics, YouTube provides a dynamic platform for your advertising needs. Always follow Google’s advertising policies and the technical ad specs to ensure your ads perform their best. Ready to start using YouTube ads? Contact us today to get started!

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Why We Are Always ‘Clicking to Buy’, According to Psychologists

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Why We Are Always 'Clicking to Buy', According to Psychologists

Amazon pillows.

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A deeper dive into data, personalization and Copilots

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A deeper dive into data, personalization and Copilots

Salesforce launched a collection of new, generative AI-related products at Connections in Chicago this week. They included new Einstein Copilots for marketers and merchants and Einstein Personalization.

To better understand, not only the potential impact of the new products, but the evolving Salesforce architecture, we sat down with Bobby Jania, CMO, Marketing Cloud.

Dig deeper: Salesforce piles on the Einstein Copilots

Salesforce’s evolving architecture

It’s hard to deny that Salesforce likes coming up with new names for platforms and products (what happened to Customer 360?) and this can sometimes make the observer wonder if something is brand new, or old but with a brand new name. In particular, what exactly is Einstein 1 and how is it related to Salesforce Data Cloud?

“Data Cloud is built on the Einstein 1 platform,” Jania explained. “The Einstein 1 platform is our entire Salesforce platform and that includes products like Sales Cloud, Service Cloud — that it includes the original idea of Salesforce not just being in the cloud, but being multi-tenancy.”

Data Cloud — not an acquisition, of course — was built natively on that platform. It was the first product built on Hyperforce, Salesforce’s new cloud infrastructure architecture. “Since Data Cloud was on what we now call the Einstein 1 platform from Day One, it has always natively connected to, and been able to read anything in Sales Cloud, Service Cloud [and so on]. On top of that, we can now bring in, not only structured but unstructured data.”

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That’s a significant progression from the position, several years ago, when Salesforce had stitched together a platform around various acquisitions (ExactTarget, for example) that didn’t necessarily talk to each other.

“At times, what we would do is have a kind of behind-the-scenes flow where data from one product could be moved into another product,” said Jania, “but in many of those cases the data would then be in both, whereas now the data is in Data Cloud. Tableau will run natively off Data Cloud; Commerce Cloud, Service Cloud, Marketing Cloud — they’re all going to the same operational customer profile.” They’re not copying the data from Data Cloud, Jania confirmed.

Another thing to know is tit’s possible for Salesforce customers to import their own datasets into Data Cloud. “We wanted to create a federated data model,” said Jania. “If you’re using Snowflake, for example, we more or less virtually sit on your data lake. The value we add is that we will look at all your data and help you form these operational customer profiles.”

Let’s learn more about Einstein Copilot

“Copilot means that I have an assistant with me in the tool where I need to be working that contextually knows what I am trying to do and helps me at every step of the process,” Jania said.

For marketers, this might begin with a campaign brief developed with Copilot’s assistance, the identification of an audience based on the brief, and then the development of email or other content. “What’s really cool is the idea of Einstein Studio where our customers will create actions [for Copilot] that we hadn’t even thought about.”

Here’s a key insight (back to nomenclature). We reported on Copilot for markets, Copilot for merchants, Copilot for shoppers. It turns out, however, that there is just one Copilot, Einstein Copilot, and these are use cases. “There’s just one Copilot, we just add these for a little clarity; we’re going to talk about marketing use cases, about shoppers’ use cases. These are actions for the marketing use cases we built out of the box; you can build your own.”

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It’s surely going to take a little time for marketers to learn to work easily with Copilot. “There’s always time for adoption,” Jania agreed. “What is directly connected with this is, this is my ninth Connections and this one has the most hands-on training that I’ve seen since 2014 — and a lot of that is getting people using Data Cloud, using these tools rather than just being given a demo.”

What’s new about Einstein Personalization

Salesforce Einstein has been around since 2016 and many of the use cases seem to have involved personalization in various forms. What’s new?

“Einstein Personalization is a real-time decision engine and it’s going to choose next-best-action, next-best-offer. What is new is that it’s a service now that runs natively on top of Data Cloud.” A lot of real-time decision engines need their own set of data that might actually be a subset of data. “Einstein Personalization is going to look holistically at a customer and recommend a next-best-action that could be natively surfaced in Service Cloud, Sales Cloud or Marketing Cloud.”

Finally, trust

One feature of the presentations at Connections was the reassurance that, although public LLMs like ChatGPT could be selected for application to customer data, none of that data would be retained by the LLMs. Is this just a matter of written agreements? No, not just that, said Jania.

“In the Einstein Trust Layer, all of the data, when it connects to an LLM, runs through our gateway. If there was a prompt that had personally identifiable information — a credit card number, an email address — at a mimum, all that is stripped out. The LLMs do not store the output; we store the output for auditing back in Salesforce. Any output that comes back through our gateway is logged in our system; it runs through a toxicity model; and only at the end do we put PII data back into the answer. There are real pieces beyond a handshake that this data is safe.”

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