In recent years, a term started appearing across the technology world: “data monetization,” turn your data into dollars.. (as we mentioned in a previous, post, you can Find Gold in Your Data!) Businesses reacted to the hype, started spending on every solution under the sun and then… Nothing. Nada. Zilch. In many cases the revenues never materialized, buyers became frustrated with the lack of results and blamed the whole concept of data monetization. The problem is, you’ve got to avoid certain mistakes... and they’re silent killers.
In truth, data products are a great opportunity for most businesses to engage customers and create new streams of revenue. Untapped, dormant data can, when refined properly, become a crucial resource for your company. Fortunately, we’ve worked on many analytics projects ourselves, have seen these mistakes made and have put together a guide to help you avoid making them yourself.
To provide some quick insight, we thought we’d share one of the tips we’ve found most helpful when starting to create an analytics product.
Creating an elevator pitch
The term is very familiar and something as a sales (and marketing) professional I’ve practiced a lot over the years. Fortunately it’s not designed for being stuck in an elevator with someone. Rather, in a few sentences, how would you describe in a quick 30 second interaction with someone, what your product is and why it would be valuable to someone (...if you were riding in an elevator with a potential investor…)?
A great place to start crafting your pitch is by listing the key attributes you’d like your investor to understand. Get together with the other stakeholders on the project and brainstorm a list of potential functionality (self-service, drill down, direct data feeds, etc.) As this needs to be a quick pitch, it doesn’t need to be a product manifesto. Agree on the 3 to 5 key attributes that make this data product compelling and organize them into a simple statement.
As the project progresses and questions arise about its goal or purpose, refer back to the elevator pitch and ask "are the things we’re doing helping us getting closer to delivering on our elevator pitch?" It becomes gauge to measure your efforts against.
Although this is a great place to being an data product project, there are other critical decisions looming on the horizon you need to prepare yourself for. This must-read white paper will cover the essential pitfalls that analytics product teams encounter..and how to avoid them. Including:
Setting product boundaries
Users and personas
How to build an engaging analytics product
Get your free copy of “The Five Killer Mistakes Analytics Product Teams Make” white paper.