More and more often I'm asked by clients how they can improve the distribution and analytics of their pitchbooks and make the content more personal to clients. It’s not surprising that these items are near the top of their wishlist for pitchbook improvements, as once the presentation is over, no further intelligence about the pitchbook, the data, or the analysis is provided. Everything is reduced to a binary situation where you either won the deal or you didn’t, and you don’t receive any further information about what may have swayed the outcome in either direction.
Just think about the last perfect pitchbook that you prepared; hundreds of hours probably went into it before handing it over. Do you know if the client read it? How much time was spent considering it? Which sets of analysis was the most compelling? No idea, right?
These are just some of the questions that any investment banker that’s poured blood sweat and tears into a pitchbook would like to know the answers to. And, I believe that just as technology has been developed to improve content creation and workflow efficiency (such as the Pellucid platform), it won’t be too long until we're turning to tech to solve these other problems, too.
Distribution and analytics
When we hand pitchbooks over to our clients, they cease to be the living breathing things we created and become static objects. But this doesn’t need to be the case.
While it’s no small feat to add distribution and analytics tracking to pitchbook creation, advances in technology are making this more and more feasible. If you can select a distribution platform that understands pitchbook content, a wealth of data is suddenly available to you and your team.
Consider marketing automation platforms. These are sophisticated enough that they don’t only tell you who opened which emails and when, but they can even tell you when a particular person is on your site, what they clicked, and for how long they were there. Recreating something similar for pitchbook content would be immensely valuable. However, just as with marketing platforms, a deep knowledge of how all the pieces work together is critical to success.
I don’t think we’re that far away from a future where you no longer wonder if a client opened a pitchbook, but you get an alert the moment that they do and a detailed report on which sections held their attention the longest. Capturing this data in an embedded analytics platform will help you optimize content, monitor what works best for which client or deal type and let you operate from a position of power, backed by comprehensive data.
Once the data is there, personalization comes next, and again, marketing is leading the way in this. From using past purchases to inform future email campaigns to targeting audiences in specific regions based on current weather conditions, many marketing tools can now deliver exact messages at the exact time they would be best received. So how can this apply to pitchbooks?
Let’s take two simple examples
1. I don’t like this, don’t waste my time
Say you’ve presented to a particular CFO ten times over the last year. In the introduction section, you always manage to sneak a share price chart into the pitchbook. Upon investigating the analytics of how the CFO looks through your pitchbooks you notice that she skips over the share price chart (let’s face it she knows this, her options are linked to it).
The analytics from those ten pitchbooks are strongly suggesting that you personalize the pitchbook by skipping the share price chart. You’ve only got her attention for a limited time, best to use it wisely.
2. No two clients are the same
Now imagine for the same client with the CEO included in all of the same pitchbooks. The CEO and CFO have retained you to find acquisition targets, so naturally, all of those ten pitchbooks follow a similar structure.
In an acquisition target overview, the analytics show something unusual.
In every pitchbook, the CEO flips from page one to page four, and then back to page three, and then to page two.
But the CFO runs through the pages in order.
These two sets of data give you some ideas on how you could reorder the CEO’s version of the book to add extra personalization, which will likely better capture their attention and help sell your story.
Leaving the dark ages
So what’s stopping us from creating pitchbooks in this way now?
Over the past two decades, the legacy pitchbook stack has remained unaltered while technology has evolved at an astonishing speed. Pitchbook creation is hindered by the rules of Microsoft Office and remained largely untouched by the power and the flexibility of today’s business technologies and systems.
The way I see it, pitchbook creation is still in the dark ages, and it’s time to evolve it to modern times. It’s time to apply today’s innovative technology, borrowing from what has proven to be effective in other disciplines, to make the pitchbook creation process more efficient and more impactful.
Building this solution is the focus of Pellucid. Working with our design partners—a range of investment banks from bulge brackets to smaller boutiques—we’ve iterated designs, functions, processes, and more to develop a platform that transforms your data into compelling visualizations that can be easily reused and recreated whenever they may be needed.
What would you like to see added to your pitchbook creation stack? Let me know at firstname.lastname@example.org.
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