In general, when talking about the significant increase in structured and unstructured human data and the technologies capturing it, we can take two angles; we can debate over why marketing should use it OR we can try to understand how marketing should use it to deliver sustainable value for brands and agencies.
Today, we see a lot of notes on why marketing should use data. We read that DMPs can help save and make us millions of dollars through frequency capping, retargeting and suppressions. We find that building advanced and ad-hoc segmentations by integrating offline and online data, we can achieve the ideal marketing mix to drive higher ROI. We discover that real-time and targeted re-marketing can help us with cross-sell and up-sell opportunities through every step of the customer lifecycle. We learn that by automating and optimising marketing campaigns we can deliver personalised experiences and increase conversions. We discover that by integrating 1st, 2nd & 3rd party data, we can transform our marketing to spill gold every second.
So, if all of this is true then why do we experience increased marketing wastage and ineffective marketing around us?
Recently, I tried using Airbnb to book accommodation. I went through the typical journey, but changed my mind at the checkout and ended up booking a hotel. Five days later, I received an E-mail from Airbnb passionately marketing the ‘travellers’ favourite’ places to stay in the city which I searched on Airbnb. Throughout the five days between searching on Airbnb and receiving the E-mail, I regularly experienced Airbnb online ads, targeting the city I searched on Airbnb. To satisfy my curiosity, I even clicked on one of the ads and was presented with a totally personalised webpage. Technically speaking Airbnb DMP/ CRM/ Personalisation systems have delivered everything by the book, except they failed to receive my money in-return. In conclusion, Airbnb didn’t just lose my money, but also wasted its own money spent on delivering the online ads, designing / delivering the E-mail and personalising the webpage. One of the reasons forcing Airbnb to lose its own money in a hope to get my money was its inability to marry insight with the science of data (i.e.More than 90% of the travellers leaving a hotel or an accommodation booking site at the checkout make their purchase within 12 – 24 hours).
Amazed by this discovery, I researched and analysed some of the world’s most prestigious brands. For example, whilst logged into chrome, I received ads from Google marketing “£75 ad credit when I spend £25 on my first campaign” – totally forgetting that I have already used Google Adwords Credit in the past, using the same E-mail address which I used to log into Chrome. Going through my newsfeed on Facebook, I saw messages marketing the same phone to me which I was using to surf Facebook. Throughout my research covering retail, banking, social networks, search, consumer electronics – I repeatedly found a common theme; technology-pushed-brand-chase without knowing me – without using the insights they already have about me.
All of this feels no different than a health club successfully selling swimming membership to a non-swimmer; because swimming counts as both cardio and strength training, it’s great for lungs, makes you a better runner, slashes major stress. Later on, selling swimming cap, ear care, nose clip, pool shoes, goggles, but without ever hiring a swimming instructor or giving any clue to the new member that they would need to take swimming classes to use their membership and the fancy swimming kit.
Similarly, I believe, the marketing world is subscribing to data pool and buying all sort of fancy kits without learning how to swim. The result is simple – more wastage of money, time and resources.
I feel, it’s about time we focus our efforts on how to use data than just why use data.
As always, the core purpose of collecting, capturing and using data will remain increasing our knowledge about people, processes and systems – ultimately, helping us develop better insights to create more effective and valuable marketing solutions to solve business problems.
The below diagram illustrates how data could be organised and utilised to create more meaningful and valuable marketing.
I will close this piece with some guidelines that can help us uncover ways to increase marketing effectiveness and reduce marketing wastage through intelligent use of data.
1. Develop Data Strategy Aligned with Business Objectives
Although it sounds very basic, but I have seen many examples of data strategies being developed and implemented in isolation. All data conversations should begin after understanding short-term and longer-term business priorities. Once business priorities have been clearly established all efforts shall be applied on identifying areas where data can support the business objectives. Considering the nature of the business, multiple action plans may be developed to support the overall data strategy. For example, for a bank, the application of data may require different attention for business, current, and credit customers. An FMCG company may require different data action plans for beauty, food and drinks verticals to support the overall strategic objectives.
2. Identify Data Sources
Understanding which data inputs are required to help materialise the data strategy is probably one of the most important and usually overlooked areas. It doesn’t need to be an overly complicated task, but can be achieved by preparing a simple file detailing;
- Business KPIs
- Business Verticals
- Data proposition for different business verticals
- 1st, 2nd, & 3rd party data requirements
- Who owns the data (internally and externally)?
- What data do we have access to and what needs to be sourced?
3. Consolidate, connect and operate
Organising and consolidating multiple data points into one place is the first step towards bringing the data strategy to life. Today, many off-the-shelf modern Marketing Clouds & Data Management Platforms are at our disposal (Adobe, Oracle, Google) to help speed up this process. Although it’s critical to build a company’s own consolidated 'blackbox', many organisations fail to plan the operational support required to run their blackbox, resulting in organisation's inability to make any use out of it. Therefore, before building a blackbox, resource audit must be conducted detailing internal and external resource requirements for the ongoing management and development of data management, distribution and analytical systems.
4. Fuel Decision Journey with Intelligence
To materialise the data strategy, many organisations rush to building traits, segments (ghost profiles) and connecting the data signals without actively using any real insights. Defining behaviours, traits and audience segments is a critical task; however, it's useless if it's not based on any real insights. Analysing the data we already have to build basic logics can significantly help to minimise the wastage and increase marketing effectiveness. To achieve this, we could start with mapping all the data we have connected to the data management or personalisation systems and applying analytics to it to reveal insights. The following diagram could be a helpful start to map and analyse different data points across the customer decision journey.
After collecting real insights across the Customer Decision Journey efforts should be applied covering two core areas;
i. Empower the communication planning process to enrich content and execution decisions.
ii. Set-up, configure and implement data technology based on insight led traits, segments, scenarios and profiles.
5. Establish Always-on Analytics & Insight Centre
Machines are good at predicting, humans are good at making the machines predict the right thing, at the right time and place. After developing and implementing the basic data systems and processes, they should be actively improved and evolved by applying real-time analytics and insights. Instead of trying to measure and analyse everything, start from the business, marketing and communications objectives and align metrics to ensure we remain focused on the stuff that matters.
The above guidelines are not intended to be exhaustive, but hopefully they will help us in understanding how to develop practical data-driven solutions to solve business problems, reduce marketing wastage and increase marketing effectiveness.