CX and marketing tech
- Posted on November 2, 2018
- Estimated reading time 5 minutes
This post was originally published in CXM.
Research suggests that great Customer Experience can bring up to three times RoI for the business, but for most companies this is not a reality. Expectations are high, but results are often disappointing.
Avanade’s recent global research with Sitecore found martech stacks are failing Customer Experience on a grand scale. We surveyed 1,440 CIOs, CTOs, CMOs and other senior marketing and IT decision makers. Sixty percent of the companies surveyed reported losing revenue because of digital marketing technology not working properly, or a lack of collaboration between marketing and IT.
Ninety-five percent of organisations say their CX is in critical need of improvement, but they don’t know how.
Up until now, companies could achieve some degree of CX success by implementing Customer Experience (CE) and Customer Relationship Management (CRM) platforms, but those days are over. It’s customers that are now in charge.
Achieving CX success can only be achieved through building an emotional connection with customers. This requires advanced insight into customer journeys and this is why applying Machine Learning (ML) and Artificial Intelligence (AI) techniques in a CX lifecycle are paramount to CX success. Eighty-six percent of respondents to our survey agree with this, but most have yet to adopt them. The bad news is that only 33 percent of IT respondents are familiar with martech and believe in including AI in their martech stack.
These results support our findings from earlier research on human-centred AI, which shows that 88 percent of respondents say they don’t know how to use AI, even though 60 percent believe AI will help companies to build an emotional connection with their customers.
Companies building martech stack without detailed understanding of their digital landscape and a solid strategy face an overwhelming number of choices, and you can choose from thousands of platforms, tools, and apps. Today’s marketing technology landscape comprises of nearly 5,000 companies and solutions, but there is no such thing as a perfect marketing technology stack.
Having an effective digital strategy is non-negotiable in today’s ultra-competitive market. Having clarity around a company’s digital as-is capabilities is critical to develop the right digital strategy.
Companies need detailed understanding of their digital landscape at different points in the company’s digital journey, to understand what next steps to take. It is output of this assessment that feeds into critical workstreams like customer journeys, content, organisation, technology, data, and analytics. Similarly, such assessments help to shape simplified, centralised solutions that combine and optimise IT and marketing to drive more sales opportunities and enhance Customer Experience.
Many major software vendors and their acquirers are attempting to accommodate centralisation by acquiring complementary marketing products, offering a centralised tech stack via a marketing cloud. Whilst many marketers still prefer using stacks that utilise several vendors, a centralised cloud based martech stack, which is designed based on a company’s strategic needs has powerful advantages.
Cloud environments enable improved IT resource allocation, security and flexibility, while centralisation equips marketers with deeper and more meaningful insights into customer behaviour. This enables them to engage in more efficient and effective marketing, creating a unified view of customers as opposed to the fragmented view that can come from choosing one of the 5,000 separate martech stacks.
Without an optimised martech stack, companies struggle to deliver a consistent CX, leaving money on the table – a situation reported by 60 percent of marketing respondents in our survey.
Incorporating AI technology into the martech stack will be critical for marketers to create value and personalisation. Through AI, marketers can analyse larger amounts of personalised data to create personalised experiences. A total of 65 percent of marketing leaders agree that their businesses are not mature enough when it comes to personalising their customers’ experience; a clear sign for the need of AI driven CX.
Whilst AI makes decisions, ML makes predictions, particularly in relation to complex, non-linear patterns, accommodating the full spectrum of purchasing behaviour rather than just reiterating a binary choice. ML is now beginning to be applied to digital advertising and marketing, supplying personalised content, creating e-commerce recommendations, predicting customer churn, and creating new applications and informing C-level strategy.
An example of this is programmatic ad buying, where software is used to automate the buying and placement of online ads.
Over three quarters (77 percent) of respondents to our survey concede that their organisation needs support in order to implement and integrate machine learning. This support comes in the form of data. Successful ML implementation needs catalogued business processes. The C-suite needs to collect as much data as possible to help make strategic decisions. Automation and machine learning only work well when the available data can inform the correct decision.
However, we found that 66 percent of marketing leaders agree that their businesses are not mature enough when it comes to data and analytics (57 percent US vs 74 percent in the UK) and this disparity will slow AI adoption further.
Organisations need to address these disconnects within the martech stack; that’s data, analytics, AI and machine learning. With machine learning, organisations will finally see the importance of the data they’ve been collecting; identifying trends and informing key decisions.
To avoid CX failure, companies must rethink their CX priorities. They need to start by gaining a better understanding of their customers, bringing emotion into the design of their customer journeys. They also need to carefully assess their digital as-is state before making technology decisions.
Furthermore, businesses need to rethink their martech priorities, leveraging AI, ML and analytics to build the foundations for successful CX. These technologies are key to helping identify customer needs, improving customer experiences and making marketing technology future ready. Increased collaboration between key IT and marketing leaders is also part of the equation, and identifying trusted partners is critical to building strong customer connections and helping these traditional cost centres transform themselves into core drivers of revenue.
To achieve success, organisations need to revise their team skills. In order to implement the best martech stack to improve CX, businesses will require a mix of skillsets integrating IT and marketing perspectives. IT decision makers need to think like marketers and vice versa, yet according to our research – there is a long way to go: 61 percent of IT respondents say marketing personnel do not receive martech training, and 70 percent of IT respondents want to improve their martech stacks but don’t know where to start.
IT and marketing must align to leverage the right technology stack and co-create a digital strategy that prioritises a customer-centric, personalised approach. According to IDC, Worldwide spending on cognitive systems and AI will reach $57.6 billion in 2021. With AI informed cloud-based martech at the centre of considerable CX opportunities, companies will start to reap the benefits of driving a great customer experience fit for their future growth plans.