When it comes to multi-channel campaign and customer data, Forrester states that though 78 per cent of marketers consider data driven marketing strategic, 70 per cent think they have poor quality or inconsistent customer data. In the worst case, when marketers cannot fully trust their data, they may end up taking action based on erroneous insight.
In the days when marketing data was scarce, intuition and gut-based marketing reigned supreme. However, with the technology stacks available today, marketing teams are awash with data.
“Data-driven” marketing has been a buzzword for a long time. The idea is simple: leverage data to make informed marketing decisions. Analytically-inclined marketers have effectively won the intuition versus data-driven insights mindshare battle. But what good is that data if it’s not trusted? Most mature marketing tools will have powerful reporting, visualisation or querying capabilities in isolation. Many of these systems have APIs to power data warehouses, and may even provide powerful applications of predictive analytics. Surely a marketer can trust the data and insights generated within that controlled environment, right?
Two issues affecting trust in marketing data
When it comes to fully trusting the data they have, there are two main issues marketers face:
Marketing leaders are now more concerned with insights that span channels – especially because the interplay of channels is what gets your consumer to convert in the end. The challenge is that individual channels are often handled by point solutions, which in turn create data silos. On average, marketing leaders today say 34 per cent of their budget is spent on channels they didn’t know existed five years ago — and they expect that to reach 40 per cent by 2019. Channel proliferation is staying – which means more point solutions, more data silos, more complexity.
Business Intelligence systems can result in sluggish onboarding and it often takes months, even years to aggregate all the data. Every time the marketer invests in a new channel, another bespoke integration needs to be built. Similarly, if you have new questions to ask, you need to rely on technical colleagues to write the queries to support your analysis.
There is sluggish insight with BI systems often updating infrequently through a batch process. If you need answers to something that’s happened today, good luck. You’re likely going to be waiting 36 hours for your result, this can lead to erosion of trust and actionability.
To overcome these issues there are four pillars that should underpin every marketer’s analytics program to increase your trust in your marketing data.
To achieve a comprehensive view of marketing investments, data needs to all come together into a unified place. Transparency and data ownership are key parts of your marketing ideas. A marketing analytics and attribution solution can provide the technical infrastructure that automates the integration of media, delivery and engagement data across 100+ martech systems, brings them together and de-duplicates across channels so you have the most accurate unified view of the customer journey.
People and the processes need to also be aligned. In order to obtain a comprehensive view of marketing, all relevant parts of the marketing organisation (and their respective agencies) need to agree. You can pull data from disparate teams’ channel-specific systems into a consolidated data store either through data APIs or by trafficking event trackers. Furthermore, campaign metadata needs to be high-quality and standardised, so make sure your teams are aware of your data quality standards and that you enforce data quality processes to avoid ingesting garbage metadata.
Marketers won’t trust a marketing analytics and attribution solution if the newest channels are constantly missing from it. New channel onboarding must be seamless, and time-to-insight must be quick.
Marketing analytics tools need to be designed for the marketer, and not require the constant intervention of the IT department to manually build queries to answer new types of questions, or to view the data in a different way. Visual analytics tools, KPI builders, custom report builders and other marketer-friendly tools may make your data look “presentable” but they also need to facilitate the marketer’s monitoring and discovery processes.
Finally, we spoke about how sluggish insights erode trust. When marketing data is continuously updated, then marketers can analyse and react to campaign trends as the campaign is unfolding. Marketers should demand real-time data in order to surface the real-time insights necessary to perform in-flight optimisation.
Data integrity is defined as the assurance of the accuracy and consistency of data over its lifecycle. The unique challenge that a marketing analytics and attribution solution tackles is to ensure data integrity as it ingests data that spans across many different systems.
When data from another system is brought into a marketing analytics and attribution solution, the integration platform needs to possess deep knowledge of the entities and schema of the source system. Marketers can try to obtain that expertise on a one-off basis – but an integration platform would have already developed that expertise from doing that integration for dozens of other brands.
A marketing analytics and attribution solution requires careful mapping to ensure that it doesn’t create mismatched data sets when consolidating data from multiple data sources into an aggregating system. Everything must be painstakingly normalised, so that all the data ingested into the marketing analytics and attribution solution creates equal comparison, and trust in the integrity of the data is preserved.
Marketing leaders must create processes to onboard new channels and maintain the data-driven mindset by bringing in folks to handle new channels in also a data-driven, rather than intuition-driven way. They need to be vigilant in enforcing continued data quality standards through a well-run governance process.
So marketing leaders – once you’ve established the three pillars of trust, ensure that your tech, process and people are in place to preserve the trustworthiness of your marketing data over time.
Florian Gramshammer, MD EMEA, Impact
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