Simplifying data across martech tools
Updated: Dec 3, 2021
Marketers are being pushed to deliver more campaigns, more leads, and more conversions in an attempt to maintain revenues in difficult conditions. There is an unrelenting push for speed not just in terms of delivering campaigns but also in terms of speed of conversion. In most organisations marketers are using 20+ marketing tools on a regular basis.
A typical marketing stack includes the Customer Relationship Management Platform (CRM), Website Content Management System (CMS), Social Platforms, Paid Advertising Platforms, Email Marketing Tools, Collaboration Tools, Web/App Analytics, Behavioural Analytics, Event Management Platform, Webinar Platform and this list goes on and on. A typical Marketing Stack for a mid to large business is shown to the right.
With so many platforms in play, the results from a March 2021 survey of over 300 marketers found that marketers are spending on average 13 hours/week on manual processes with a major contributor being manually working with data and analytics across tools.
Marketers crave data to inform decision making and optimise campaign and engagement performance. In the current environments it’s no longer a lack of data, in fact there is a mountain of data available. The new challenge is to join the data from across different platforms and tools, to create a full 360 degree view which can deliver insights at the speed required by high performing marketing teams.
The traditional solution has been to bring in centralised analytics teams, to create custom data pipelines that fill data warehouses, then have highly specialised data analysts use complex BI tools like PowerBI and Tableau to create a series of dashboards for marketers to look at. The problem is that this approach is slow, disconnected, expensive and frustrating for both sides. Marketers still can’t access the data with the speed that they need, the tools available make it too difficult to ask questions, and the analytics teams become swamped with a never ending stream of questions that aren’t answered by the pre-created dashboards.
The new solution to the longstanding problem is two-fold:
Create no-code or low code connections to allow the data from these different platforms to be joined together
Provide a search driven BI tool that has been designed from the ground up for marketers (not analysts) to be able to ask their own questions of data
Combining Data Across Marketing Tools
No-code or low-code integration hubs provide a way to extract data from a platform, to reformat the data and to combine it with data from other platforms, without the need to write custom code. This is great, as it means it is achievable for marketing teams without the need to be reliant on programers or technical teams and it means there isn’t the ongoing headache of managing custom code.
Analytics and Reporting for Marketers
Static dashboards are dead. The need and expectation for a marketer to be able to ask their own questions of data is here. But slapping the same old tools in the hands of a marketer and hoping for the best, is not going to deliver. Search and AI driven tools that have been designed for business users, like ThoughtSpot, are what is actually empowering and delivering insights for marketers. ThoughtSpot’s simple search bar allows you to type your question in simple language and get an answer in the form of a chart of visualisation.
Bringing it together in a single solution
And the icing on the cake? That’s bringing the two parts together. Enter - Pivot. Pivot is the union of the low code integration hub and ThoughtSpot. Pivot has out of the box support for a range of CRMs, Web/App Analytics, Social Platforms and Collaboration tools like JIRA. It’s as simple as logging into your marketing tools to get your data connected and get searching and answering your own questions. If you would like to find out how marketers can get the answers to their own questions, take a look at Pivot - Marketing.
With Pivot, marketing teams are no longer wasting hours every week, manually fighting with data in Excel spreadsheets, to try to piece together marketing analytics. Pivot provides the ability for marketers to ask questions of data on the fly and finally have insights at the speed needed to optimise campaign performance and customer conversion.
