The B2B Marketer's Guide to Data Science
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Transcript of The B2B Marketer's Guide to Data Science
Order of Play
What is data science?
What problems does it solve?
Okay but what marketing problems does it solve?
What can I, the humble marketer, do with this information?
Life-changing takeaways
What is data science?
page 04
It is / a method of deriving insight, meaning and value from large amounts of data. For example: / all your marketing data / big external datasets / a way of emulating human-quality research at scale. For example: / browsing the websites of every potential prospect and deciding whether or not they’re in segment
What is data science?
page 05
Big Data
Data science is how you extract value from
using certain tools, such as:
Your CRM
Machine learning
Natural language processing
Data mining
What problems does it solve?
page 06
Loads, but examples include: / Predicting churn / Basket abandonment / Who in the company you should be targeting / What products you should be selling / Predicting value
What marketing problems does it solve?
page 09
As we’ve said, plenty. But these are the big two: 1 It can extract enormous value from your CRM / Usually a mash-up of closed-won/losts, customer surveys, marketing automation and data bought in from third parties / Data science can derive insights, and thereby bring value, to this otherwise overwhelming and often messy dataset
What marketing problems does it solve?
page 010
As we’ve said, plenty. But these are the big two: 2 It can find all your best prospects (outside your CRM) / Companies House data, SIC codes, are out of date, inaccurate and incomplete (but it’s not their fault – they were never meant for this purpose!) / They cause huge problems for sales and marketing further down the funnel / Poor conversion rates / Time spent calling the wrong prospects / False picture of your market
How does it solve those problems?
page 011
By emulating human-quality research at scale: / It removes the need to rely on SIC Codes / Instead it allows you to rely on primary sources of data / any text placed online, such as website source code / This gives you a much more accurate overview of your market / And it’s not just about who, but about when
What can I do with this information?
page 012
Collecting primary sources of data and deriving insights from it is not a job for marketing. / Companies who provide this solution often call themselves ‘predictive marketers’ / Massively overused term… / Marketers have been predicting for as long as marketing has existed / Some PMs also buy-in third-party data, meaning you’d be back to square one, but a bit poorer
What can I do with this information?
page 013
How to choose an effective data provider: / Some questions you must ask: / “Do you have full coverage of my market?” / “Do you use SIC codes or do you have a different way of representing industries/sectors?” / “Do you measure the accuracy of your data?” / “How often are these metrics updated?” / “Are you reliant on third-party data providers?”
Life-changing takeaways
page 014
There are plenty of reasons that data science is important, but the single biggest reason it matters to marketers is: / It means having high quality market data / And as long as you ask the right questions, you will: / Get a more accurate picture of your market / Spend less time contacting the wrong prospects / Increase conversion rates/rate of first meetings