Optimise the customer journey with data driven insight
Earlier this year Aberdeen ran a fantastic webinar entitled Optimise the Customer Journey with Data-Driven Insight.
The key finding of the Aberdeen study was that organisations today are rich in data but poor in insights. Capturing data alone is not enough, organisations must be able to take clear action from their data if they are to succeed.
Aberdeen revealed that best-in-class businesses using customer analytics enjoy superior results across customer experience (CX), marketing, sales, service and financial measures.
- 39x improvement in customer lifetime value
- 39% improvement in cross-sell/up-sell value
- 2.6x improvement in customer satisfaction rates
In line with these statistics, and those from across the industry, our own experience demonstrates that businesses harnessing data-driven insight are achieving:
- 38% more prospects and opportunities
- 24% uplift in accelerated sales results
- 40% improvement in productivity
- 34% improvement in relevance and credibility
Turning data into action is the vital ingredient when it comes to optimising the customer journey, and harnessing tools that drive insight-driven change is therefore key to helping your business succeed in today’s customer centric IT economy.
In this blog I will give you 8 ways you can optimise the customer journey with data driven insight. But before we get to that, what is customer journey optimisation and why do you need to do it?
Defining customer journey optimisation
Customer journey optimisation is the process of connecting and mapping customer interactions, across multiple touchpoints, in order to direct or influence the end-to-end experience.
To do this well businesses must create opportunities for more personalised, relevant and consistent messaging at every touch point with the customer. Data driven insight is the information that informs the journey.
According to Aberdeen organisations that use analytics are maximising performance across all aspects of customer interaction are reaping the rewards when compared to those that don’t:
- 84% customer retention rate compared to 53%
- 1% year-on-year improvement in customer satisfaction rate compared to -6.6%
- 4% year-on-year growth in annual company revenue compared to -6.1%
- 8% year-on-year improvement in average customer profit margin compared to -7.5%
Looking at these statistics the business case for optimising the customer journey with data-driven insight becomes startlingly clear.
8 ways to optimise the customer journey with data driven insight
Build a single view of the customer
According to Aberdeen creating a unified view of the customer is fundamental, and best-in-class organisations start the customer journey optimisation process by building a single view of customer insights.
By building a single customer view, sellers are better able to understand how the purchases, interactions, and behaviours of customers will drive future actions. They can therefore target them more effectively with the most appropriate messages at the optimum time.
This insight helps sales and marketing teams produce more effective strategies and campaigns, improves the quality of every engagement, and the crafting of relevant content that resonates with the customer agenda.
It is important that this single view is shared across the business and that they understand the customer journey and how they can help shape customer experiences in order to optimise it.
The implementation of artificial intelligence (AI) technologies such as advanced analytics, machine learning and natural language processing mean that organisations now have the ability to cut through the copious amounts of raw data generated every day – from corporate information, news and social media to research trends and influencer opinions to build a 360° single view of the customer.
Additionally, they’re providing a way to identify ‘propensity to buy’ based on a deeper understanding of buyer personas and sentiment analysis, along with the best time and way to contact them, and which product or service will resonate most.
Likewise, they’re helping to enhance personalised engagements, solutions and experiences by tapping into data on needs, pain points and aspirations.
Building a single view is the foundation of customer journey optimisation, a platform upon which to build all sales, marketing, business development and customer success activities. The benefits to name just a few being:
- Tailored and timely communications
- Deeper understanding customer needs, wants and preferences
- Merging of understanding across the business
- More beneficial relationships based on insight
- More targeted product development
- Greater value per customer through improved identification of cross and up- selling opportunities
Do more with data – turn insight into action
It’s not the collection of data in itself that’s useful, it’s what you ultimately can do with it.
Emerging capabilities in data analytics, data modelling, machine based learning and natural language processing are no longer just filtering data into insight, but interpreting data and directing action – fundamentally disrupting the way sellers actually sell.
So why does turning insight into action help optimise the customer journey? Here’s a three practical examples:
Lead generation – Gaining an understanding of experiential factors from the news, views and opinions a prospect has been generating allows sellers to build much more targeted and accurate sets of measures and triggers that can be used to perfect lead generation and sales execution.
Sales meetings and presentations – Marshalling exactly the right facts at the right time can sometimes make the difference between success and failure in meetings and presentations. Having a constant supply of precise and up-to-the-minute insights can help augment sales calls with a useful contextual anecdote at the vital moment, or capture and hold the attention of a room by understanding the sentiments and expectations of everyone around the table.
Act on new opportunities – Identification of an insight trigger such a news story about a customer may suggest they would be receptive to a call or the delivery of information about a product or service that provides a solution for a problem or need at the exact moment they have it.
Translating data into insight, and enabling insight to be turned into actions optimises the customer journey by delivering improved, personalised and contextually aware customer experiences that ultimately drive more business – win, win.
Maximise performance across all aspects of customer interaction
We now have endless opportunities to interact with customers, whether it be email, print, phone, social media, face-to-face, live chat, text or app.
Aberdeen’s study reports that most 51% of companies use at least 8 channels as part of their customer experience programmes, but only 17% are full satisfied with their ability to harness data as part of this omni-channel strategy.
A key finding of the study was that technology is a key enabler when it comes to maximising performance across all aspects of customer interaction. This using business intelligence, customer intelligence, customer analytics, predictive analytics and machine learning report that they’re twice as likely to be satisfied with their ability to use data to manage customer interactions. Why?
Because discovering useable information about customers is far less onerous. No longer do sellers have to navigate into the depths of CRM systems and interpret some semi-relevant chart, instead sales acceleration software will simply sends you the specific information you want in an instant. Whether it be quantitative such as latest financial information, or qualitative such as an interesting nugget of information to kick start a new conversation.
The combination of big-data and AI offers the opportunity to analyse and curate relevant content from millions of sources to deliver usable insights to sellers fingertips at exactly the moment they need them, as well as providing them with a simple solution for acting on the information whether it be sharing the content across social media, sending a well-timed email or picking up the phone for a value added discussion.
According to Aberdeen the results for businesses optimising the customer journey by harnessing data-driven insights to maximise the potential of every interaction are vast – improvements in average handle time, bigger returns on marketing spend, high customer conversions and win-back rates, higher customer retention, and improved sales team attainment.
Interact with customers in a more contextually aware manner
Nothing will turn a customer off quicker than offering them irrelevant products or services.
For any customer interaction to succeed it must deliver the highest degree of relevancy possible – it must be relevant to the customer need and what’s happening in their business right now, it should augment or improve their business and their relationship with yours.
Importantly sellers must understand and demonstrate why the product or service will make a difference to the customer – why they need it, why it differs from other products or services they currently use or might consider using, any gaps in their business it will fill, how they will interact with it, how it will deliver value.
True contextual relevance comes from having the power to determine in advance what a customer needs, and what product or service will have the greatest impact.
Prediction is a key B2B sales skill, and AI modelling, predictive analytics and machine learning are making life easier by helping to identify patterns of event types, market challenges and new opportunities even amongst the longest term and best understood customers.
Offering the opportunity to not only predict need, analyse what solution will have the greatest impact, and even the most likely response.
The result – improved understanding of relevance and therefore enhanced ability to interact with customers in a more contextually aware manner and optimise the customer journey.
Deliver consistent messages
Customers expect and demand superior experiences on a consistent basis, businesses today cannot go at buyers with conflicting messages delivered by different teams running separate playbooks across multiple channels.
Everyone needs the same view of the customer journey if they are to optimise it – that single view again. Doing this without access data driven insight is going to be a challenge. But more than that it requires all parts of the business to work together, again technology is an enabler.
Technology is rapidly transforming sales, marketing, business development and customer success alignment. Smart use of intelligence and insight tools can improve understanding of the customer, improve lead qualification and prioritisation, aid successful conversions and pinpoint new opportunities to engage and add value throughout the customer journey.
But more than this smart use of technology can bring every part, and every individual within a business closer together and in doing so ensure they better serve the customer and optimise the customer journey.
Best-in-class businesses are furnishing sales, marketing, business development and customer success teams with a single view of the customer from both internal and external data, and providing them with tools to consistently address customer needs at each stage of the sales funnel (both pre- and post-sale) in order to anticipate enquiries and offer lightning-fast responses and recommendations, improve inbound marketing efforts and outbound sales tactics, and boost customer success.
Predict and model behaviour to map the customer journey
According to Aberdeen best in class businesses are:
- Using predictive analytics to map sentiments and behaviours
- Creating models of customer buying behaviour
- Building customer playbooks to support sales efforts – predicting the next steps in the customer journey in order to move it along
Machine learning and predictive algorithms can enable sellers to construct models based on patterns of event types and customer attributes, that correlate more or less with eventual success.
When sellers know exactly what the next steps are, they can better predict success and avoid failure, resulting in more sophisticated sales strategies, campaigns, and product or service development.
As time goes by and the volume of data improves precision and predictive capacity, these models will advance, enabling faster and more accurate predictions of customer needs, pain, market challenges and opportunities – before customers themselves even realise what lies ahead – not just optimising the customer journey but influencing the direction of travel.
Empower sellers – give them the insight they need to do their job
AI-powered sales intelligence solutions can help sell more, sell faster and sell smarter, and importantly save money for the businesses that deploy them.
Utilising machines to automate key activities such as information gathering, research on buying behaviours and trends, due diligence, and answering customer questions in real-time, leaves sellers free to undertake more strategic decision making and human-touch relationship building tasks with an even greater level of clarity.
Data-driven insight helps sellers get more creative, make better management decisions, and spend more time doing what they do best – engaging with customers.
Aberdeen provides a great example – Take a sales team of 200, each earning an average salary of £50k per year. If each spends a typical 14% of time every day on research and administrative tasks then that translates to £1.4 million in unnecessary costs to the business each year.
Time and money that could be better spent optimising the customer journey.
Gauge performance to exceed expectations
A great salesperson knows their strengths and weaknesses, and finds ways to fill the gaps.
They adopt new behaviours, seek out opportunities to direct their strengths to best effect, and learn how to manage their weaknesses in order to work in the best interests of the customer.
Aberdeen agrees saying that the best sellers use analytics to track their own performance and exceed expectations by analysing which aspects of customer interaction influence customer behaviour.
AI and MBL concepts provide an ideal set of techniques with which to analyse and model the actions and outcomes behaviours with each customer, in order to pinpoint those which are most successful.
Likewise, the same approach can identify the opposite actions or inactions that typically correlate with failure.
This information can then be used to improve behaviours, correct mistakes, adapt selling style to each customer, and better align with customer needs.
Start optimising the customer journey
I’ve outlined eight ways you can optimise the customer journey with data-driven insight.
Artesian offers the perfect platform from which to start your optimisation journey – just look at the results achieved by BT Local Business as a result of embedding Artesian within their sales and business development strategy.