Mike Ferguson is VP Global Services and GM EMEA at customer data platform company Redpoint. We caught up with Mike to find out what his day-to-day role entails, as well as his thoughts on identity resolution, first-party data, AI and omnichannel marketing.

Tell me about your role – what does a typical day look like for you?

As the VP of Global Services, my role covers teams based in each of our key regions: APAC, EMEA and North America.  Every day is very full, so before I start work, I make sure that I get some exercise: a run or some yoga.  When I am in the UK, I start my day with a quick meeting with representatives from our APAC and EMEA implementation teams.  As the US comes online through the day, the teams check-in. 

Each day is a combination of driving plans to continue to scale Redpoint to meet demand, meetings with customers and partners, and implementation of reviews to make sure that projects stay on track and clients realise the benefits of their investment in Redpoint. 

What are some of the biggest challenges still associated with CDPs and how can companies overcome them?

The challenge continues to be the realisation of identity resolution from a wide range of data sources with variable data quality. We see customers facing challenges in bringing together data from the digital world with the in-store data and resolving that data to a person or household – ultimately creating robust, effective digital footprints for each consumer. 

With so many vendors in the CDP space, it is concerning to see some that are deprioritising the identity resolution challenge. This is not good for customers as it builds up a customer data debt that will be ineffective for marketing and difficult to resolve. 

How will data strategies evolve in the next 12 months?

We believe that data is foundational to executing omnichannel marketing experiences and delivering relevant and personalised interactions across any customer touchpoint. Without a deep, accurate and real-time understanding of customers, personalisation will fall short of its potential ROI impact. And this understanding is only gained through a focus on improving the quality of data – fit-for-purpose customer data will be key in effective data strategies for 2023 and beyond. 

Additionally, with third-party cookies and customer reference files going away, there will be an increased emphasis on monetising first-party data for brands. This will require an uptick in data quality capabilities to make sure that data is accurately connected across various identifiers and in the cadence of the customer journey. This is critical to providing highly relevant offers and messages via a personalised customer experience, which is also increasingly important in driving revenue as new customer acquisition faces headwinds (higher costs, lower results).  

Brands also will need to use automated recommendations to tailor messages and offers at the individual consumer level to drive higher relevance, ensuring that consumers see value in providing zero- and first-party data. Personal data needs to be respected with high data security and privacy and be implemented with the type of intelligent orchestration that delivers a consistent personalised experience in an omnichannel way. 

As brands look to monetise their customer data, data clean rooms will become more widely used and will put more pressure on software vendors to facilitate consent, value exchange, compliance, and cross-entity collaboration to generate new revenue streams. 

How might generative AI impact CX in the future?

In the short term, AI will continue to grow in usage as it is successfully applied to specific high-value use cases, for example to personalise offers and content, detect anomalies, and predict segments. In the future, AI will likely play a bigger role in creating individualised content, interacting with customers via chatbots for text and voice, metaverse, augmented reality, and predicting preferences based on a customer’s usage trends, seasonality, or external factors. 

There will also be AI failures that in turn guide the market to more nuanced and advanced uses of AI that will shape the future as much as the successes. One failure will be in marketers using AI as a blunt instrument to solve general problems vs. a surgical tool to improve individual consumer experiences. Software vendors, like Redpoint, that can help brands execute high value AI use cases, have the depth of customer profile capabilities to best feed quality data as fuel into AI, and can take advantage of the innovations in third-party AI platforms. 

AI and machine learning enables brands to utilise software to simply outline the outcomes, and let AI construct, through trained best practice, the most effective approach – whether it’s to maximise revenue, engagement, brand affinity or profit. Marketers have proven over the past couple of decades that they want to focus on the goal of increasing ROI, and technology – though vital – has managed to get in the way as much as it has helped. AI will allow marketers to achieve this focus, and potentially run most of their marketing efforts for them – “lights out marketing” – that can include everything from the segments and journeys required, to the actual content delivered.

The more brands can focus on strategy and continuous fine tuning to drive a true market of one, the more personalised the customer experience will become. 

What other trends or innovations do you think will come to the forefront in the next 12 months?

Where companies in the retail and travel industries have been early to adopt multichannel marketing technologies, we will increasingly see organisations from many other industries stretch the use cases to support dynamic customer journeys, for example, real-time omnichannel use cases across all journey stages and channels, across marketing and operations.

From healthcare to insurance and from financial services to media companies, the interest in omnichannel marketing solutions is growing, and we see each industry bifurcating into winners and losers: the winners will make the shift from organisation-centric and product-centric to truly customer-centric.   

Each industry needs to think about transforming CX to be customer, patient, donor, subscriber centered. Those who do it well will win, and those who don’t will lose.  This has led to more demand for such things as vertical-specific templates, predictive models, data structures and connectors.

Security and privacy requirements will vary by industry and verticals also want to incorporate channels and front-line employees in different ways, requiring that any data solutions also be configurable to the specific industry needs.   

Customer Data Platforms Best Practice Guide