The Media and Entertainment Intelligence Playbook

We’ve gone from a world of mass media marketing to an audience of one. Must-see films, one-size-fits-all cable packages, and appointment TV have been replaced by personally curated media that’s consumed anytime, anywhere on any number of devices.

In an environment where the consumer is king and expectations are at an all-time high, global media and entertainment (M&E) companies need to refocus business models to offer tailored, curated experiences whilst also streamlining internal processes.

M&E companies are used to pitching their products to audiences of billions. Now, they need to pitch products to billions of individuals – and do so effectively at scale. Change is always hard, but research shows that putting the customer at the centre boils down to three primary challenges:

• Budgetary constraints
• Engaging with customers in real time
• Innovation

To innovate and engage with customers in real time, analytics and data insights must be the core driver of all engagement. It’s arguably the most important resource in business. Nearly all analytics and IT decision makers surveyed (92%) in our State of Data and Analytics Report say trustworthy data is needed more than ever before. Data quality is one of the top concerns for M&E industry leaders, as well.

However, outdated backend systems combined with the onslaught of mergers and acquisitions within the M&E industry often means that data and teams are disconnected, siloed, and unable to reach their full potential. Organisations with data siloed across systems (23%), partially integrated with gaps (23%) or a strategy in place but not in progress (36%) still remain. The work to create a data foundation at the outset is necessary for future AI initiatives.

If M&E organisations want to truly take advantage of data, they need to do more than just possess it. They need to go from an ecosystem of individual departments with their own KPIs and priorities with their own manual processes to one in which everyone works together and efficiently to create a cohesive customer journey.

How do you make this shift? How can you garner new insights and use data to drive intelligent decision-making? The answer lies in pulling three important levers that:

• Unlock data
• Understand data
• Take action with data
• Automate business processes

Unlocking data enables M&E organisations to get a 360-degree view so that they can put the customer first and gain a deep understanding of every interaction and preference throughout the journey. This includes calls, page views, campaign interactions, event attendance, buying power, product or service use, and anything else that would help to identify and predict what customers need, when they need it, and why.

Acquisitions are now commonplace across the M&E industry. Whether it’s a big communications company buying a content brand or media powerhouse scooping up several smaller organisations, these acquisitions require complex merging of teams, data, processes, and systems. Unsurprisingly, this creates internal challenges. When different departments use different technology systems, it is difficult to easily share common information.

The average organisation now uses 991 different applications , and many of these systems are poorly connected. The same research shows that the resulting data silos are a barrier to creating integrated user experiences for 90% of organisations.

Vast systems of disconnected data are problematic. Customers expect streamlined experiences, from subscriptions to streaming services to online publications. Siloed data prevents cross-team collaboration, which in turn makes it impossible for M&E organisations to get a true 360-degree view of the consumer.

How do you fix this? The solution lies in connected systems built on the foundation of a lean tech stack coupled with an API strategy. Organisations that can build this kind of application network will realise their success in a “data domino effect.”

A strong data culture hinges on a lean tech stack that doesn’t rely on legacy technology. The transition typically starts with replatforming in the cloud. This is where developers implement agile, modular architectures that incorporate reusable data sets. In other words, it consolidates the number of tools your employees need to do their work well.

Once you’ve done this, you’ll need to ensure it’s all integrated into a solid customer relationship platform (CRM). With a leaner tech stack in place, the benefits will become immediately apparent: IT will be able to experiment faster, deliver more effectively, and stay ahead of business needs.

APIs unlock data from disparate systems so you can organise and orchestrate it. This allows different applications to talk to each other and ultimately makes it possible to work from a single platform.

In the M&E industry, an API strategy means you can deliver content to audiences in a format that’s compatible with whatever device they prefer. M&E companies can also facilitate seamless exposure to content across any device from multiple back-end systems, allowing them to deliver a smooth multi-screen viewing experience.

This is where Salesforce can help. Salesforce focusses on building a complete strategy that takes CRM, integration, and data into account so that you can:

• Connect data from any system – no matter where it lives – and deliver critical, time-sensitive projects.
• Use discoverable, reusable APIs and integrations to ensure business continuity by scaling to meet digital demand and solve operational gaps.
• Increase speed and agility to create connected experiences and allow companies to handle unprecedented change and unpredictable needs.

For more information on how your business can implement the right integration strategy and supporting architecture, learn about MuleSoft . Once you’ve done this, you’ll need to ensure it’s all integrated into a solid customer relationship platform (CRM). With a leaner tech stack in place, the benefits will become immediately apparent: IT will be able to experiment faster, deliver more effectively, and stay ahead of business needs.

Despite access to more data than ever before, synthesising and making sense of data is still a challenge. This is where artificial intelligence (AI) can help by drawing on your integrated data to provide valuable insights. This gives you the ability to make informed, data-driven decisions with the help of AI and answer important questions like:

• Where are the opportunities to grow revenue?
• What is my pipeline and funnel health?
• Who is a churn risk?
• How do I deliver the best consumer experience?

When media teams visualise data, they immediately understand how content is being consumed and are able to evaluate its success . To do this, teams can generate real-time, easily understandable daily insights about target audiences and consumer preferences. For example, making sense of audience sociodemographic, behavioural, and consumption data informs B2C retention strategies, augmented by AI, and opens the door to upselling advertisers. They also quickly respond to changing patterns of demand, manage customer churn, and predict which expansion strategies will be most profitable – all with the help of AI.

M&E organisations can use data to instantly answer complex business questions and uncover solutions. Because these insights are native to a CRM platform, business users don’t waste time hopping between systems to find answers.That may include using AI to provide insight into how different versions of your content performed with different audiences or how marketing campaigns promoting an event performed. Out-of-the-box analytics templates and apps also help you get up and running quickly with intelligent experiences, reducing the burden on IT. Tasks that used to take days to complete can now be accomplished by a single individual in a matter of minutes.

This connected system provides a unified view of investments, performances, and outcomes across channels to make data-driven decisions. So if you’re an advertiser struggling with a complex ecosystem of brand partners, agencies, and systems, you can view ad sales data, identify and eliminate inefficient spend, and allocate budget to the most effective and efficient campaigns, channels, messages, and audiences. As a result, you are better equipped to drive brand awareness, acquisition, cross-selling, and loyalty.

Imagine studios under pressure to be more efficient in content distribution. They can use AI to predict marketing performance, perform more targeted A/B tests, and even use it to remove inefficiencies in their operations to bring their creative work to market faster.

M&E companies can use AI to keep up with the evolving consumer landscape and address behaviours and needs in real time. There are two ways to think about action and implementation: predictively and prescriptively. That’s because AI helps M&E organisations keep up with the evolving consumer landscape and market dynamics and address behaviours and needs in real time.

Predictive intelligence mines through large volumes of data to identify valuable relationships between cause and effect. It uses those patterns and relationships to make educated predictions. This makes it possible for an M&E company to anticipate behaviours and create and maintain a more personalised customer experience in these ways:

• You have insight into how marketing affects factors such as leads and open pipelines by region, segment, and product.
• You can use historical browsing and purchase data to predict which channels, content, products, and messaging will garner the best response.
• You can create custom models that predict churn risk, likelihood to convert, delayed payments, and lifetime value.

Prescriptive action describes the process by which AI uses predictions to suggest a range of actions that improve outcomes. When combined with predictive analytics, prescriptive action can suggest options that take advantage of future opportunities while mitigating future risks. Here are a few common examples for M&E organisations:

• You have the ability to adjust campaigns to better target audiences and get a better ROI.
• You can surface specific content or offers based on previous engagements as well as viewing history.
• You can create personalised journeys for predefined customers. So, if you have a segment likely to churn, you can anticipate it and proactively take them on a personalised, win-back journey.

The M&E industry is becoming more and more complex not only with the need to personalise experiences but also the wide-range and ever-evolving set of business processes it takes to survive. Automation gives media companies an edge when it comes to navigating these complexities by streamlining things like:

• Subscriber management to ensure your customers are consistently engaging with your content, while flagging those who are at risk for cancellation. Churn prevention automation can detect when a subscriber finishes a series and seamlessly suggest similar content without requiring human input. Additionally, AI can autonomously monitor service interruptions, streaming quality, and viewer experience metrics that could frustrate users. When potential churn risks are detected, AI can trigger an automated retention strategy, creating and delivering personalised communications with acknowledgements of issues, exclusive offers, and relevant content recommendations, ensuring that the entire process is optimised for minimal manual oversight and maximum customer retention.
• Advertising sales across countless platforms, continually adapting based on performance, and always-on transparency with the buyer. You can automate tasks such as tracking available ad space, optimising pricing, and scheduling ads to ensure maximum fill rates and revenue, along with delivering insights and automatically adjusting campaigns to improve ROI.
• Order fulfilment in ecommerce, which is now a critical part of the business when it comes to revenue diversification. An automated order management system starts working as soon as a customer places an order and it’s automatically routed to the appropriate fulfilment centre or digital delivery system. It manages all of the logistics, such as locating the nearest warehouse with available inventory to reduce shipping time and costs. Shipping coordination — such as the generation of labels, pickup schedules, and tracking — saves time and gives customers transparency into the process.

Moving core business processes onto an AI-powered automation platform takes manual and complex processes off the plates of teams, allowing them to focus on more business-critical tasks while increasing efficiency, reducing costs, and optimising the customer experience.

Of the companies that have implemented automation, over half report improved employee productivity (59%), employee experience (52%), and customer experience (49%). Still, many media companies have yet to implement this technology. These key operations are still generally described as manual by many organisations: churn prediction (46%), subscriber acquisition (36%), and advertising sales (25%).

Autonomous agents, a new type of software capable of performing work at various levels of autonomy, is the next step companies can take with their data. Agentforce, deeply integrated in the Headless 360 platform and powered by AI, data, and action, can meet customer needs by executing tasks on their own or seamlessly handing them off to an employee. Agents can help across every role, from sales, service, marketing, commerce, and more.

What does that mean for your organisation? Agents can be set up with out-of-the-box capabilities for sales or service. A service agent can field an enquiry from a customer at any time on any platform – for example, if a customer has a billing question – and independently answer questions. Sales agents can respond to leads around the clock, for example, an RFP from an ad seller – provide personalised responses, handle rejections, and seamlessly hand warm leads off to human reps.

Or with Agent Builder, you can build an agent into just about any workflow, from licensing to subscriber experience to troubleshooting to any order management step. You can use existing Salesforce Platform tools to create standard and custom topics and actions grounded in your trusted data.