Imagine your marketing team has published forty articles in a year. It has launched campaigns, sent newsletters and created new content for social media. Yet website traffic is falling, downloadable resources are barely generating any sign-ups and, when it is time to present the results, the same old question comes up: how many business opportunities have we generated?
Your team spent weeks defining the ideal customer profile, analysing purchase intent signals and selecting the accounts with the greatest potential. Marketing did its job. Sales managed to open conversations. Everything suggested that the opportunity would eventually turn into business.
Last week, in our article “The Complete Account-Based Marketing (ABM) Guide for Technology Companies (I)”, you discovered what ABM really is (and what it isn’t), why this strategy fits perfectly within the B2B technology sector, and the three levels of personalisation —One-to-One, One-to-Few and One-to-Many— to help you choose the model that best suits your resources and objectives.
Your sales team chases 200 leads. Only 3 close. Sound familiar?
Account-Based Marketing (ABM) campaign optimization has taken a significant leap forward thanks to the use of predictive models based on artificial intelligence (AI).
