Don’t Bore Us—Get to the Chorus!

Lead with conclusions in your data marketing content to drive data discovery and usage, demonstrate data integrity, and support data monetization.

Mar 25, 2024

Welcome to the Data Score newsletter, composed by DataChorus LLC. The newsletter is your go-to source for insights into the world of data-driven decision-making. Whether you're an insight seeker, a unique data company, a software-as-a-service provider, or an investor, this newsletter is for you. I'm Jason DeRise, a seasoned expert in the field of data-driven insights. As one of the first 10 members of UBS Evidence Lab, I was at the forefront of pioneering new ways to generate actionable insights from alternative data. Before that, I successfully built a sell-side equity research franchise based on proprietary data and non-consensus insights. After moving on from UBS Evidence Lab, I’ve remained active in the intersection of data, technology, and financial insights. Through my extensive experience as a purchaser and creator of data, I have gained a unique perspective, which I am sharing through the newsletter.

In order to monetize data products, data companies need to get the message out that 1) their proprietary data exists, 2) it can be used to answer important questions, and 3) their data has high integrity.

However, the target audience for these messages is time-constrained and overmarketed. How can a data company get the message out?

Following these 4 pieces of advice when creating data marketing content will allow for improved engagement, supporting the case to monetize the data product.

Content as a product: Achieve an Outcome, Solve a Problem, and Deliver Value
Create a great “hook for the chorus”
Keep It Simple for the Reader
Measure Content Performance and Adapt

The article will expand on the complications facing creators of data marketing content as they try to get the attention of a time-constrained audience. It will then go into each piece of advice in more detail, providing examples to bring the concepts to life. It will also expand on items to avoid before wrapping up with a call to action to measure the performance of content in order to adapt.

Treat your content like a product. A product delivers value to the consumers of the product. A product achieves a job to be done.

As always, The Data Score Newsletter is the start of the conversation.

For data companies, do you already incorporate these ideas into your content strategy?
For consumers of data content, what other approaches do you appreciate from content creators to allow you to get value from it?

Content as a product: Achieve an Outcome, Solve a Problem, and Deliver Value

Treat your content like a product. A product not only delivers value to its consumers but also fulfills a specific need or “job to be done.” The same is true for your data marketing content.

Lead with the conclusion and let the audience decide if they want to dig in deeper.

Identify audience needs

A secret of institutional investors1 that outsiders wouldn’t necessarily understand: Finance professionals are reading constantly for a living. Annual reports, earnings releases, news, sellside2 research, internal research, trader commentary, and all the emails. Some of my former buyside clients shared with me that they would receive between 500 and 1,000 emails a day. But here’s the counterintuitive point: They don’t actually read; they scan.

There just isn’t enough time to consume everything that could be useful and there is also a lot of noise compared to the signals in the available information. So, highly productive finance professionals have to be good at discerning what is worth their time.

For content to add value to an investment professional, it has to be clear why it’s important and then quickly deliver the outcome. If it’s still adding value, the reader will continue to consume the content. Once it’s no longer adding value, they move on to the next source of information.

Be clear on the outcomes to achieve

For content to add value to an investment professional, it has to be clear why it’s important and then quickly deliver the outcome.

Taking a product mindset to content means your outcomes and target audience should be predefined. It is important to be clear about the outcome to be delivered before creating the content. Also, target your content to the appropriate audience persona based on their “jobs to be done.”

There are 4 types of outcomes: data discovery, data use cases, data integrity, and data monetization.

For the target audience, there are different functional roles as well as different personas. Personas include “Insight Seekers” or “Data Junkies,” and “Data Professional.” There’s a fourth persona: “Never satisfied,” but let’s park that for another time.

Please note that the “Data Professional” persona would have more overlap with specific data roles in sourcing, design, and engineering than other personas, which would spread across more roles.

Data Discovery: alerting the audience that your data product exists. This type of content helps data scouting and data sourcing professionals know your data product is available and also lets data junkies know there could be new data to play with to discover new insights. Services like the Initial Data Offering (IDO) share information about data products being made available, with high-level information about what makes the data special and useful.
Data use cases: in this type of content, the data provider demonstrates the value of the data by using it to answer highly relevant questions, delivering the answer to the question with their data. This is ideal for information seekers who want to find new insights. Unlike data discovery content, data use case content is less concerned with what the data product is and more focused on how it delivers value to users. I would note that while the content may be valuable for insight seekers and data junkies, the use case content may not be exactly what the data junkies on the buyside need, as they are often the ones tasked with generating the insights. It is more valuable to them if the content sparks ideas for novel approaches to creating insights with data rather than just the answer itself.
Data integrity: this type of content shows that the data product can be trusted because of its methodology, including a focus on what makes the data product highly compliant with industry best practices and risk standards. This can include more details on what makes the methodology unique. It’s also important to be transparent about the limits of the data and use cases to avoid. Back-testing analytics will be part of this type of content.
- This content is ideal for “insight seekers” in particular. For the insight seeker who is keen to get the answer to the questions on their mind, having supporting information to allow them to trust the data behind the insight is important.
- While sourcing professionals will absolutely care and want to see details on the methodology, they are likely to ultimately be the ones who decide for the firm if they believe the data has integrity. They will follow their process for assessing data integrity. And while it wouldn’t be bad to send them this content, know that they will be more interested in their due diligence questionnaire and back-testing process.
Data monetization: this is the selling content. It shares the commercial terms and makes the case for why it’s worth paying for the data product. It’s important to keep the goal of this content separate from other types of content. Finance professionals understand that they want to be able to count on the data in the long term. They know the data company must be economically solvent and therefore receive appropriate compensation for the data product that meets the budget constraints and shares the ROI3 with the data vendor. Part of data monetization is providing instructions on how to access the data, which should be clearly included in the monetization content. It is ok to cross-reference the other 3 types of content but make sure the outcome of the email is focused on the win-win economics of the data product.

The start of the process begins with knowing the outcome before creating the content. At the end of the content creation process, it is important to ensure that value is likely to be delivered. It’s easy to get lost in the details. Come back to the idea of the content as a product.

Understand the audience’s pain points and context

It’s critical to understand each cohort’s process and painpoints to properly understand their jobs to be done. Let’s consider the “Data use case” outcome. It’s important to make sure the nuance of the outcome from the audience’s point of view is understood and captured in the content.

A common data use case story: the data can predict the quarter

1. Considering signal to noise.

One aspect of this is understanding how accurate the answers need to be for the outcome needed.

An example of this is presenting data that could be used to predict quarterly financial results. Showing the model and margin of error4 with high accuracy is undermined when the accuracy range is wider than the consensus estimate range5. Imagine a dataset that is said to predict a retailer’s same store sales (a KPI6 for retailers that removes the impact of new and closed stores on revenue growth).

For a new data point to be valuable, it must narrow the range of possibilities.

If the consensus forecast for same-store sales growth is 3.0%, with the highest estimate at 3.3% and the lowest at 2.7%, the total range spans 60 basis points.
If a dataset is used to predict, the answer is 3.1%, but the margin of error for the estimate is 200 bps, so the prediction is adding noise and not signal.
In instances where the audience's uncertainty is high, even a 200-basis-point margin of error could provide valuable clarity, highlighting the importance of context in assessment. If the consensus was 3.0% but the range from top to bottom was 0% to 6%, the 200 basis point margin of error with the new data is valuable.

2. Focus on what matters to the audience

At times, content may dwell on issues that hold little relevance for the audience. Being very accurate on something that can’t make a difference to the valuation will lead to low engagement. Sometimes content providers can provide very accurate answers on a company’s financial performance, but they only cover 5% of the business.

Can there be cases where data on a small part of the business would matter? What actually matters is the contribution to overall marginal growth. In the right circumstances, it is possible for accurate data on a small part of an overall story to resonate.

In order to try to explain the concept of marginal contribution, I’m going to use a made-up example. One where the data shows a large enough difference in growth in the small business such that the overall headline is affected compared to an example where the change in the small business doesn’t add up to a material difference in the headline.

Material contribution: If a business is growing revenue 6.7% y/y with a tight consensus range, and the 5% of the business covered by the data is growing revenue 20% y/y while everyone is expecting the small business revenue growth to be 0% y/y, that would be material because it’s going to add 100 bps to the consensus growth rate that no one expects and generate a revenue estimate that beats (all else equal in this made-up example).
Immaterial contribution: In contrast, if the dataset's prediction of 0.3% yearly growth in the small part of the business barely exceeds the 0.0% consensus, its impact is minimal and not materially significant.

Focus on the marginal growth and the impact on the overall outcome.

3. The importance of debates changes over time in financial markets.

As debates are answered with the market agreeing on the answer, it becomes reflected in the share price, so the market moves on to the next debate. It’s important to know where the debate is to properly frame content.

It’s ok if the content is about the old debate (debates eventually come back around to being very important), but the content has to be framed to acknowledge this. Perhaps revenue growth is no longer the primary debate and margins are now the primary debate.

The content could be framed as the following in this made-up example:

“After last week’s results confirmed high revenue growth in the prior quarter, our data continues to show the trend remains in line with consensus expectations for this quarter. However, our data points show revenue growth acclerating in lower margin categories. If it continues, it would lower the margin realized if the trend continued. We’ll check the data in 4 weeks to see if this business mix shift continues.”

By acknowledging that the primary debate has shifted from revenue but the data can help understand the new debate, even tangentially, it would be better received by the audience.

A few things to avoid

Don’t create click bait

We are treating content as a product that adds value. To me, that’s the opposite of clickbait. A great hook should create that itch to learn more, but it’s important to satisfy the reader with the outcome they are expecting. Clickbait to just drive clicks and not provide value has negative implications for your brand. Mailchimp offers some impact of clickbait headlines

High Bounce Rates
Decreased trust in your brand
Decreased engagment
Negative impact on search engine rankings

Source: https://mailchimp.com/resources/clickbait-headlines/

Don’t skip the caveats or constraints, or stretch beyond best practices on compliance and regulations

There’s no such thing as a perfect data product that answers all questions. There are inherent limitations and caveats to any data product. Be honest about this by being clear about what the data is good for and what it cannot do.

This includes staying within the regulatory and compliance constraints of data products, which could include how personal identifying information (PII)7 or material non-public information (MNPI)8 is handled. There’s so many good use cases for data products within the best practices of data integrity that there’s no need to even veer into the grey areas of compliance and regulations.

Keep your outcomes communicated in the data content within the caveats, constraints, compliance, and regluations.

Don’t push for a “yes” to buy as your starting point of the content

Each piece of content in an overall content strategy should have a specific outcome in mind for the reader. Therefore, it is best not to conflate the goal of selling data with the other outcomes of data discovery, data use, and data integrity.

Content that is about monetizing the data is a valid piece of content, but know that the audience is going to see the content as a selling effort. If you combine the selling with content about data discovery, data use, or data integrity, it distracts from the outcomes of those content items.

Efforts to sell before showing value are easy to spot and are likely to have less engagement. If you show value in your data content and the users are able to generate value from your data product in their trials and ongoing use, it is appropriate to create content to help move forward to commercial discussions.

Create a great “hook for the chorus”

Be like Aerosmith and get to the chorus as fast as possible. Deliver value to the reader right away so they decide to keep engaging with the content.Use engaging introductions

Learning from popular music

Dave Grohl of Foo Fighters and Nirvana once sat down with Kyle Glass of Tenacious D to share some tips about writing popular music. He made a great observation about one of the great American rock bands: Aerosmith. “What is the verse of ‘Love in an Elevator?’ It’s all chorus!” I’m not sure Dave Grohl would have ever imagined that his insights on music creation would keep showing up in a blog about data-driven insights. He finished with the adage known in the world of writing music as “Don’t bore us—get to the chorus!”

I think the adage is true for popular music because there is limited bandwidth for most consumers of media. There are so many choices for music, movies, podcasts, books, substacks, data newsletters, etc. But there is not enough time to consume it all. Even in the days of terrestrial radio, the next station was a dial-turn away.

That’s not to say that there isn’t a place for longer formats and dynamically challenging music, or, in our world, deep dives into a data topic. A demand for detailed information from the audience indicates strong engagement, warranting the availability of in-depth material. However, it’s important to not lead with the details. Lead with the conclusion and let the audience decide if they want to dig in deeper. (Also, thanks for deciding to dig in deeper since you are still reading this far!)

The hook of the chorus matters a lot!

A clever headline, but not too clever

The content must immediately demonstrate its value to persuade business readers, especially investors, to invest more time. The “hook” is the answer to the implicit question any reader has when they see an email subject, a white paper title or a LinkedIn post's first line: “Why should I care about this?”

Be clever with the hook, but not too clever. As I’m writing this, I wonder if I did well with “Don’t bore us—get to the chorus” as the headline. Maybe not everyone in the audience has heard that phrase before, but perhaps the audience will remember a time when they really liked the main part of the song with the catchy melody and clever lyrics, but they really didn’t care for the rest of the song and skipped ahead to the chorus.

Be like Aerosmith and get to the chorus as fast as possible. Deliver value to the reader right away so they decide to keep engaging with the content.
Leading with the conclusion is really important. Don’t bury the answer in the body of the content.
Sometimes there needs to be a bit of context first to make the conclusion really hit home and starting with a question is also a great way to establish the hook.

Leading with a key question and an immediate answer works to draw the reader in.

A critical question already on the mind of the reader means any answer will be valuable. That’s why critical, unanswered questions are so powerful. The reader cares a lot about the question and doesn’t know the answer. They are probably working actively to figure out the answer during their working hours. Seeing the same question they care about will immediately allow the reader to identify the potential for value in spending more time with the content beyond the headline.

This is especially true for professional investors. They may be in an investment position and have a specific thesis of what will happen to move the share price to their view. They are constantly looking for clues that they are right or wrong. They are not trying to win an argument; they are trying to generate returns. If they are proved wrong, they will simply exit the investment and move on to the next one. They want to find out early.

Consider a long-term growth investor who has held an investment for many quarters and years based on the view of constant high sales and earning growth compared to other companies in a sector. They would absolutely want to know if the story changed, but it’s also important to them to know that nothing has changed in their thesis and the company is on the same path. Because they always worry the story could be different, knowing it’s the same is valuable.

Of course, breaking news of a change in trend is way more exciting and seeing the answer to the question that something is newly discovered as different from the status quo will always draw in a large audience. But it’s rare that the stars will align to accurately disprove the consensus in one piece of content. Know that the content doesn’t need to meet that standard to be valuable.

Once we get past the headline portion of the hook, the next text has to reaffirm to the reader that there is value in continuing. Provide the answer to the question quickly and give the highlights of why the answer is right.

Situation, complication, resolution

A well-known structure for business audiences is to begin communications with the situation, then introduce a complication, and then offer the resolution.

Start with the situation, which is something that should be common ground with the audience.
Introduce the complication, which the audience will identify with. It may be a complication that they are already aware of or something new to them.
Provide the resolution, which is the answer or solution to the complication. The resolution is the longer part of the format compared to the situation and the complication, which are just enough information to make sure the reader is aligned with the value to be delivered in the resolution.

This simple structure actually borrows from a well-known structure in story-telling called the Hero’s Journey.

For more on the Hero’s Journey and to realize almost all of your favorite stories follow this format, check out https://www.novel-software.com/heros-journey-examples/

Source: https://www.novel-software.com/heros-journey-examples/

The good news is that you don’t need to take your audience through a near-death experience to return with the “elixir” of your data products.

However, the above is simplified into: situation, complication, resolution. And it’s ideal for communication with business audiences.

The situation and complication structure provide enough context so that the audience can start from the necessary understanding to understand why the resolution is so important rather than jumping straight to the resolution.

This article uses situation, complication, and resolution

Actually, did you notice that the beginning of this article actually started with this format. This time I’m showing it with the labels.

Situation: In order to monetize data products, data companies need to get the message out that 1) their proprietary data exists, 2) it can be used to answer important questions, and 3) their data has high integrity.
Complication: However, the target audience for these messages is time-constrained and overmarketed. How can a data company get the message out?
Resolution: Following these 4 pieces of advice when creating data marketing content will allow for improved engagement, supporting the case to monetize the data product.
- 1. Content as a product: Achieve an Outcome, Solve a Problem, and Deliver Value
- 2. Create a great “hook for the chorus”
- 3. Keep It Simple for the Reader
- 4. Measure Content Performance and Adapt

Is it a negative to use a commonly used framework? no

You might have recognized this familiar template upon first reading, likely finding it a comfortable framework. It made it easy to relate to what the article was about.

If you didn’t notice it was that format, even if you are aware of the structure, it probably felt natural as part of story telling that we are all used to.

It’s not something that will be seen as a negative if the formula is followed. There’s plenty of room for creativity within the structure. And, it can also help remove some writers blocks if the template provides the building blocks to get started.

Also, when you think about more complicated story-telling and all those movies you love, it doesn’t actually detract from your enjoyment that they are following a well-established formula, right? Don’t be shy about using this structure to communicate; it works.

Keep It Simple for the Reader

Simplify Complex Information

We’ve decided on the target audience and the outcome for the content in advance. We’ve crafted the hook and chorus that set up the conclusion.

Now the content needs to follow through on that promise of value. In the resolution, there is likely to be a complex narrative to share with supporting points. In the resolution, it is easy to get lost in the details, but the below offers suggestions on how to keep the message easy for the audience to digest.

Know your audience and speak their language

A common theme throughout the Data Score Newsletter has been breaking down the language differences between financial, business, data, and tech professionals. All cohorts use too much jargon. Using common language helps improve collaboration, but if there’s only a few moments to get a financial reader’s attention, value needs to be delivered in their terms and language.

Use the Pyramid Principle to organize the resolution

We discussed the situation, complication, and resolution framework. The resolution piece has a bit more substance to build out to make sure the message resonates with the reader and the value is achieved.

Using the Pyramid Principle will allow business readers to understand the conclusion and get the value. It starts with the conclusion and then builds top down with supporting points—three supporting points is ideal. Each of those points can have supporting points; all of them need to be mutually exclusive and fully exhaustive.

Lead with conclusions, not methodology. The pyramid principle avoids the common problem with content, which is writing up the steps the writer followed to create the outcome. That’s leading with methodology, not leading with conclusions. Leading with methodology buries the so-what so deep in the text that the reader misses the point. Not only should we lead with conclusions at the top of the content, but each section and paragraph should lead with a conclusion.
Mutually exclusive: keep ideas separate so its easy for readers to follow the point of each section. Jumping from idea to idea makes it harder for the reader to follow along with the information. If the 3 supporting points chosen lead to a complex reference between the supporting points while explaining the conclusion, it’s likely that the 3 supporting points are not properly grouped together and should be reframed. This applies further down the pyrnimd. Each supporting point may in turn have 3 supporting points and those should be mutually exclusive from the other branches of the pyramid.
Fully exhaustive: If the reader knows there’s more aspects to the content than covered by the content, it leaves an unanswered question lingering in the reader’s mind, which distracts from the value delivered. It doesn’t mean every supporting point needs to be covered in full detail; it just needs to be acknowledged.

Early in my sellside analyst career, a mentor introduced me to this impactful concept and book. It helped me become a much better business writer and effective sell side analyst. Those who have worked with me know I’ve paid it forward by sharing the book and concepts as we co-created content. This will be a topic I come back to in future Data Score Newsletter entries to get deeper into. Here’s a link to the book: https://www.amazon.com/Pyramid-Principle-Logic-Writing-Thinking/dp/0273710516

Hero charts that stand on their own

A picture says a thousand words. Having a single chart that tells the story is highly impactful, but that chart needs to have all the relevant information within it to be effective. It also needs to be easy to read, so what needs to jump off the page.

Take the made-up example above. The calculations shown there are meant to make the point about how to think about marginal impact clear from a mathematical point of view (big changes in small businesses can matter).

But if I were to try to create a hero chart, it would look something like this:

Example hero chart with made-up data and scenario

The chart shows the data compared to consensus. In the chart, there are only 4 columns (including the 0.0% column for the consensus small business revenue growth).
There’s a “call out” with an arrow point out the “so-what” for the total business. There’s a note giving more information, caveating an assumption about the 7.7% derivation since the made-up data company only has visibility on 5% of the business.
I thought about making it just 2 columns for an even more simple takeaway, but I thought that since this made-up data company only has 5% of the business covered, it made sense to all show the strength of the data.

I am open to feedback if you have it on the hero chart!

Measure Content Performance and Adapt

Create feedback loops with data on your audience’s behavior as well as anecdotal feedback to adapt your content strategy.

Track Engagement Metrics

Measuring content performance is crucial for adapting strategies to amplify what works and revise what doesn't.

To know if if the content strategy is resonating, track the following items:

Open rates
Click-through rates
Time with content
Repeat engagers

The measures above will reveal if the content is adding value. Time-constrained readers will stop reading or not open the content in the first place if they are not seeing the value provided by the content. Make sure to measure by content outcome type and audience personas.

Implement Feedback

A/B test where possible to see what works to improve each of these metrics. Importantly, make sure you are balancing volume measures like open rates with quality measures like time with content and repeat engagements.

A/B testing, also known as split testing, is a method of comparing two versions of a webpage or content piece against each other to determine which one performs better. It involves showing the two variants (A and B, where one is designed to be the control in the experiment) to similar audiences and comparing their engagement and conversion metrics.

How frequent should content be? Follow the metrics

In addition to the contradiction of investment professionals needing to read consistently but not actually reading everything, there’s another contradiction. Investment professionals will tell you they get too many emails. They are right, but what they leave out is that they get too many low-value emails. Investment professionals prioritize their time, focusing on content that delivers substantial value and bypassing lesser content.

There are content providers who do send emailed content daily and generate a high impact without being seen, which is part of the noise of “too many emails.”So, it is possible, if you add value, to have a high frequency of delivery.

Keep in mind that everyone thinks their content is of high value when they write it. That’s why the data is important to follow. If the content is too frequent relative to the value it provides, open rates are going to fall. If some content is more valuable than others, engagement metrics will show it.

Find the cadence that’s right for your product and audience while tailoring content for different personas.

Concluding thoughts

This article attempted to walk through the challenge of getting content heard amidst the noise with my own experience creating content as a sellside analyst and creating data marketing content. Treat your data marketing content as a product that delivers value, leads with conclusions, and keeps it simple for the reader. Adapt your content strategy based on the data and feedback.

This isn’t a one-size-fits-all.

What other approaches have worked for your content?
For consumers of data marketing content, what resonates most with you?

The Data Score