I’m here with Rahim Hajee, Chief Technology Strategy Officer at Adastra to discuss the emerging concept of Customer 720, and how it can be beneficial for organizations to get a more complete picture of their customers and therefore provide them with a higher degree of personalized services.
Hi Rahim. First off, can you explain the concept of Customer 720 and how it came about?
Definitely. Customer 720 is an evolution of the term Customer 360, which is a domain-specific sub-term for a master data management (MDM) system. A Customer 360 solution shows a holistic view of cleansed, de-duplicated, mastered, and governed customer data across multiple systems as they relate to accounts, products, brokers, or other domain-centric MDM solutions.
There are two views on the evolution of Customer 360 to Customer 720. One is that Customer 720 consists of two circles: the first circle being internal customer data and the second circle being external customer data. The second circle consists of information that maps your customers to their social media profiles (e.g., Do they have a LinkedIn profile? How active are they? Are they tweeting about your brand?), loyalty information, channel preferences, and marketing campaigns. This information helps us get an understanding of how to engage with that customer.
At Adastra, however, we like to say that Customer 720 is the evolutionary combination of a master data management platform and a customer journey platform, leveraging deep AI and ML-driven segmentation to drive analytical capabilities and enhance the customer experience through derived actions. This information reveals the next best action recommendations and ways to personalize customer journeys. So, it's not necessarily two circles that complement each other, but it’s a tiered process – aiming to get more out of that 360 or 720 MDM experience with each layer.
Breaking down these tiers further, the customer journey platform allows us to capture omnichannel interactions that a customer has with your organization. Did they go into the store? Did they call the call center? Did they interact through your website? Did they use your chatbot? Did they make a purchase? Having this transactional and behavioural data allows us to enhance our customer master record and understand whether each interaction with a customer is positive or negative.
Then, we can use AI and ML to assess each interaction and its impact on key KPIs, revealing the next best actions to take to enhance customer loyalty and brand affinity and get to a deeper level of personalization. For example, if they had a negative experience, perhaps there are further discounts that can be automatically applied to their current transaction, or if they are repeat customers with a high lifetime value, perhaps advanced notifications of new merchandise or additional bundling savings are target campaigns that can resonate with the customer.
The end game is customer loyalty, growth, and cost optimization.
OK, so I think you touched on this, but can you articulate the benefits of Customer 720?
Absolutely. Building on the key themes of customer loyalty, growth, and cost optimization, the goal of Customer 360 is to gain a better understanding of your customers. This means how many your organization has, which accounts belong to your customers, what products they have, how to contact them, preferred channels, who their internal representatives are, and contractual information. Organizations can also implement a mechanism to attain key metrics or key performance indicators (KPIs).
With Customer 720, we enhance this by understanding their holistic journey across our organization and through customer micro-segmentation. This allows us to improve cross-sell and upsell opportunities by creating offers or products that will resonate specifically with customers. We can address customer needs more effectively to ensure every interaction is a positive one.
It allows organizations to identify friction points that might exist. If, for example, customers can’t buy a product from the website or there are a lot of call center interactions because alternative channels are not available, then we can focus our efforts on finding that channel optimization mix to increase customer satisfaction.
From a cost perspective, it can help optimize the cost to acquire and retain a customer, resolve customer issues through AI-based automation efforts, or even help figure out how to create a new product that resonates with customers, reducing research and development and trial and error efforts.
With Customer 720, organizations can potentially have dynamic pricing through bundles or subscribe and save models, passing additional benefits to the customer. The idea here is to have this done automatically, leveraging what you know about your customer (taking into consideration customer lifetime, loyalty, and relevant micro-segments), leading to higher customer retention.
Are there any challenges that organizations should look out for when implementing Customer 720?
There are a few challenges that could come up. The first one is overall data governance maturity when implementing an MDM solution. The concept of MDM ensures that key lines of business have a say in how their domains look at the end of the day and how they might interact with one another, which is both an advantage and a challenge, in addition to making sure the data is clean, accurate, matched, and deduplicated on the MDM side. Multi-domain and multiple domain MDM strategies can help alleviate this.
The other challenge would be around the segmentation of customers. How exactly are you segmenting customers? Are there any concerns that, if this type of segmentation were to be revealed publicly that it might create damage reputationally to the organization or impact loyalty from that specific customer (e.g., calling them “not a high-value customer”)?
There are some privacy legalities that exist around laws for the protection of customer data and how they might be used. There could be different criteria for personalization in terms of how we can aggregate and view these customers as well as what we can leverage for analytics from a third party or internal sources. Organizations need to ensure the right processes are in place, so they are looking at clean and accurate data.
There are also architectural challenges around the overall security of data with technologies that use, interact with, or integrate data with one another.
In essence, current market mature MDM providers have some form of remediation to these challenges built into capabilities, supporting the governance within and governance of any MDM solution.
So, is Customer 720 best suited for larger organizations with more robust data processes, or can it be leveraged in smaller organizations?
The caveat here is that if you don’t have an MDM in place and you're a large organization, it will be a little bit harder organizationally to get to Customer 720, whereas for a smaller organization, it might be easier because there will be less ownership and process change management challenges in the way.
There is value for both larger organizations and smaller organizations that want to grow and understand more about their customers. Smaller organizations don't have to implement large-scale MDM or customer journey platforms, but they can implore the techniques and methodologies when it comes to segmenting customers, having a consolidated view of their customers, and understanding what products they have at scale. This can be accomplished through data engineering principles and advanced analytics. For larger organizations, it would be best to opt for dedicated technologies that specialize in MDM, customer journeys and democratized analytics capabilities.
At the end of the day, Customer 720 is for anyone who wants to really get those core outcomes of the customer experience – optimized cost and growth.
Is there anything else that you think organizations should know about Customer 720?
I think as MDM solutions mature; Customer 720 capabilities and adoption will also mature.
When I say mature, I mean we will have direct access to social media integration, omnichannel connectors to internal and external systems, connecting call centers, CRMs, chats, industry benchmarks, and external demographic data, among other things. This is in addition to being able to represent the conflation of these sources in a digestible format that can uncover insights and drive actions.
We are almost at the level where there are out-of-the-box Customer 720 accelerators and solutions that take advantage of AI and ML to deliver advanced analytical capabilities, such as predictive insights, sentiment analysis, and natural language processing (NLP).
How can Adastra help organizations looking to implement Customer 720? Why choose Adastra?
Our heart is data and analytics and it's not limited to a specific industry or domain. It's holistic, and we've been implementing MDM solutions for the past 15 years in one form or another.
We have a very detailed methodology, accelerators, strategy guides, and delivery models to accelerate a Customer 720 journey. We have experience implementing customer journeys leveraging MDM data and creating an automated AI-based next-best-action mechanism to better serve customers and their enhance experience.
We have the experience and people behind it, and we're cheerleading the efforts to drive more value out of an MDM solution into the Customer 720 space.
Thank you, Rahim!
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