The Convergence of AI in Marketing and Sales: Creating Seamless Customer Journeys

After analyzing how AI is disrupting the traditional approach for Marketers and for Sales professionals , today, I'm going to explore how AI is breaking down silos between Marketing and sales creating seamless customer journeys that drive business growth.

Let’s face the reality: traditionally, marketing and sales have often operated in separate silos, leading to disjointed customer experiences and missed opportunities.

AI is here to help changing this paradigm by enabling a unified approach to customer engagement. There is a real opportunity for this achievement, but I believe this is going to be possible if both functions do the right steps towards the goal. Let’s see which touchpoints need to be explored and can benefit from a wise use of AI.

Where AI is getting momentum for both Marketing and sales

The first area to look at is?how we see our customers through our data and our systems. Unified customer profiles are a pivotal shift to embrace to make sure Sales and Marketing operate with a coherent customer view.

AI-powered platforms like Salesforce Customer 360 are revolutionizing how we understand our customers. By aggregating data from multiple touchpoints, these platforms create comprehensive customer profiles that both marketing and sales teams can leverage.

In my experience each time my team and I were able to share with sales a view of what the customer was doing in terms of? engagement there was either a positive discussion or at least a clear alignment on what were the next steps going to be, resulting in higher customer retention, higher speed and I the best scenario a boost in upselling opportunities.?

AI doesn't just collect data; it turns it into actionable insights. Tools like InsightSquared https://www.insightsquared.com/ ?use machine learning to analyze data from both marketing and sales, providing a holistic view of the customer journey. It is also able to capture activities and input them in the CRM. The aim for this platforms is to balance human inputs with machine learning to validate forecast and investments, know how to minimize risks and capture upsides.

An example of? what I observed in large corporations is how difficult really is to scale up a methodology for Opportunity advancement . It requires a continous analysis of the funnel to identify: a) where the customer is in his purchasing Journey and, in case of large accounts b) how to isolate and target the right person involved in the right opportunity.

Marketing automation teams can prepare paths of communication and campaign cadences that are great ( in theory) for engaging customers at a defined point in the Buying Journey. But without a unique view of the customer Marketing might miss the moment and engage the right customer at the wrong time!

Making it simple: using AI to define the right target list just as the right message gets prepared increase the confidence of delivering a timely message to the right person, avoid sales to be worried about an untimely engagement and holds everyone accountable for keeping an updated track of the customer situation in the system. ?

Another area where AI can keep sales and marketing aligned is in the area of ABM. AI excels at identifying high-value accounts for ABM campaigns. Platforms like Demandbase use AI to analyze firmographic and technographic data, helping to pinpoint the most promising target accounts.

In our organization, we used such platforms within our Marketing automation practice and through experienced agencies to build our campaigns, ?resulting in more targeted account lists and a above Industry average engagement with our top-tier accounts

But today we can do one more step: AI tools like Terminus enable coordinated, multi-channel outreach across marketing and sales teams. These platforms use AI to determine the optimal timing, channel, and messaging for each account.

Alerting on the right time to act

Another perennial challenge for marketing is how to identify ( and how to prevent ) Customer Churn -? The customer lifecycle has never been so complex to draw, understandand predict. Well, AI is transforming even how we approach customer retention.

Tools like DataRobot use machine learning to predict which customers are at risk of churning, allowing for proactive intervention.

In salesforce and most of CRM it is now easy to implement alerts that can be setup so that sales can consider taking action on customers that showed a risky behavior.? Extending this concept in a positive way? Marketing and sales can identify customers with the highest engagement at the right moment of the journey to accelerate that specific opportunity or to start a conversation when intent score shows it’s the right time to act. AI can lready suggest via AI generated Push notifications.

Not only . Talking about customer lifecycle and opportunity lifecycle AI can identify optimal upselling and cross-selling opportunities. Platforms like Xsellco use AI to analyze purchase history and behavior patterns to suggest relevant additional products or services, making this available to Customer service, E-Commerce or Online sales teams.

Who scored the point? AKA: the attribution dilemma

I wrote a lot in the past about sales & Marketing alignment alignment and one of the most difficult things is to convene on a shared model that attribute success across the customer journey.

Tools like Bizible (now part of Marketo) use machine learning to provide multi-touch attribution models, giving credit to both marketing and sales touchpoints.

I have been personally participated to a a working team that implemented a marketing attribution model based on engagement to identify the return of investment of Marketing.

We worked to understand and represent in a comprehensible way how our campaigns turned into Influenced pipeline and won pipeline though a pretty complex model. The project is based on CaliberberMind ?in the back end and helped marketing understand which campaigns , touchpoints really worked in creating and advancing engagement, and which did not turn into results that we could easily appreciate.

The beauty of AI is that it doesn't just provide insights; it continuously learns and improves. Platforms like Datorama ( now known as Marketing Cloud Intelligence in Salesforce) use machine learning to continuously optimize marketing and sales performance based on real-time data. It is designed mainly for agencies but works well for retailers and publishers as well as for the gaming industry.

Multi-Channel execution: not that easy

If that seems a lot already, think this: how does it help in a Multi-Channel world? I would say that the promise of AI is to help delivering consistent, personalized experiences across all channels.

Tools like Optimizely use AI to personalize content in real-time across web, mobile, and email channels. They embed digital asset management, CMS, a content marketing platform and more to avoid spaghetti integrations. Despite ?these are not yet integrated with the salesview they are tools for marketers only so platforms like this help providing consistency at the customer end.

AI is a great enabler and can push our boundaries where we did not ever imagine. But as we embrace AI, it's crucial to maintain ethical standards and the human element in customer interactions. At every step of our AI implementation, we've prioritized data privacy and ethical considerations, ensuring compliance with regulations like GDPR.

I can interprete a common path in all my avid readings around these considerations., and the most successful approach is to use AI to augment human capabilities, not replace them. Sales and marketing teams can use AI-generated insights to have more meaningful, personalized conversations with customers.

Get ready: prepare your organization

The convergence of AI in marketing and sales is not just a trend; it's the future of business growth. To prepare your organization for this AI-integrated future:

• Invest in robust, integrated data infrastructure
• Foster a culture of data-driven decision making across marketing and sales
• Continuously educate your teams on AI capabilities and best practices
• Prioritize ethical AI use and maintain the human touch in customer interactions

By embracing AI while maintaining our focus on delivering value to customers, we can create truly seamless customer journeys that drive business growth.

There is a "BUT"! AI brings challenges and trade-offs that I will explore in another article ( a Sequel to this trilogy!!)

There is a lot to reflect on how to use the possibilities that AI brings, including the latest revolution announced just a week ago around autonomous agents . I believe this is going to make a lot of what we know about AI obsolete!!

By now, how do you embed AI for Marketing and sales? Contact me if you want to discuss about this or share in the comments.