In the first part of this series I described how I wanted to build a CRM system for my business based around the free Hubspot CRM. In this part I’ll walk you through the steps I used to integrate data from 3 critical sources: LinkedIn, Google Contacts and other third party sources such as Lead Forensics or Event attendee lists etc.
Even without a crystal ball, I can confidently predict that much of the marketing data you use for your marketing campaigns is rotten. In my corporate career at IBM it was a constant area of frustration, as it has been in almost every client I’ve worked with over the last 4 years, irrespective of size.
In the years since I established Purple Salix, I’ve been fortunate to work with CMOs and marketing leaders of large global companies through to small startups, and across the tech sector and multiple industry sectors beyond – including Finance, Oil, and Green chemicals manufacturing. However, irrespective of size and industry, the areas of challenge are remarkably consistent. Without wishing to betray any client confidences, here are 4 of the questions that every marketing director most frequently asks me to help them address.
Yesterday I joined a webinar hosted by Laura Ramos of Forrester Research in conjunction with Idio on the topic of Predictive Analytics. Predictive Analytics is not a particularly new term – I first bumped into it several years ago with a case study where the social media analysis tools were being used to predict the outbreak of ‘flu epidemics across the US (turns out that before people retire their sick bed the last thing they do is to tweet their friends to tell them all that they’re feeling a bit snotty). The business benefit of this was that the analysis allowed you to predict an outbreak several days before people made an appointment with their doctor. For a drugs company or a medical supplies company that could provide vital intelligence to ensure that supplies were prioritised to the most-needed locations.
All of a sudden it’s very trendy to talk about data and analytics. Of course there’s very good reasons for this – the data that you capture potentialy provide an enormous amount of insight about a client’s actual and likely behaviour. However most of us are failing to capitalise on this potential.
