Accelerating Customer Growth with Artificial Intelligence
PwC’s 20th CEO Survey [i] finds that CEOs are optimistic about growth, despite concerns about volatility in the global economy. In fact, 38% are very confident about their company’s revenue growth over the next 12 months.
The landscape has undoubtedly shifted, from cost-oriented to growth-oriented. We’ve moved away from the cost-centre mentality and today, customer growth is recognised as the central catalyst for business growth.
The key challenge CEOs face now is deciding how to prioritise and maximise customer growth potential. Artificial intelligence can be at the centre of that.
Maximising customer growth options
As a business leader, the core question is this: how do you prioritise your options for customer growth?
- How do we increase market share in our existing addressable market?
- How do we sell more to our existing customers?
- How do we minimise churn and maximise customer satisfaction?
- Where are our opportunities for cross selling?
- How do we identify and prioritise the most valuable strategies for the future?
Business executives are responsible for solving these challenges, but the waters they must navigate are muddy. Competing, conflicting views from multiple stakeholders. Cross-departmental siloes. Limited, historical-only data. Too much data to meaningfully process.
The answers to these questions rest on a deeper understanding of the customer.
- What if you could accurately predict which customers are most likely to buy, and which of those will have the highest lifetime value?
- What if you could identify which existing customers are most likely to buy more, different products or services from you?
- What if you could identify which customers are likely to leave, or remain inactive – in enough time to change the outcomes?
- What if you could prioritise your growth strategies with predictive outcomes based on Customer Lifetime Value?
Luckily and unluckily, organisations today have access to vast swathes of customer data. But as much as data is the solution, it’s also the problem.
On the one hand, executives today have access to a huge range of customer signals from extensive and disparate sources. This is a revolution in customer understanding, as organisations are able to gain deeper, omnichannel insight about their customer across the entire lifecycle.
Harnessed correctly, this intelligence offers the possibility of an integrated, cross-channel understanding of the customer that helps business leaders answer the questions above.
On the other, this abundance presents its own challenges. As the Deloitte Customer Focused Growth report [ii] notes, “Finding the signal among Big Data’s noise is the key challenge”.
Organisations are overwhelmed with customer data. Sources are diverse and complex. Extensive descriptive, interactive, behavioural, and attitudinal data points interact to build an intricate picture that can be difficult to interpret, which means the transformation from data to insight is not a simple one.
The solution is using artificial intelligence to make sense of the noise, in the form of predictive analytics platforms.
Advanced predictive: making sense of Big Data noise
Advanced predictive platforms like BrightTarget sift through the noise created by Big Data to help executives better determine their customer growth options.
Predictive platforms filter millions of internal and external data points to present data in a simple, streamlined way that aids strategic decision-making.
These insights apply across the entire customer journey, from segmentation to retention to growth through to acquisition. Organisations are empowered to make decisions that generate maximum growth throughout the customer lifecycle:
Understand – Better understand customers, improving segmentation by value, behaviour or product.
BrightTarget helped a national wholesaler achieve £400K cost savings from a 44% decrease in required activity through segmentation optimisation.
Carine Jessamine, Marketing Director of Selco, “After using BrightTarget for several months, we can now predict what our customers may want in the future and align our offers accordingly, to grow our business even faster”.
Retain – Focus activity on predicted highest value accounts, delivering the right offers to the right customers. Highlight churn risk customers to optimise retention and reactivation activity.
BrightTarget helped a leading European financial publisher achieve 7% increase in renewal rate of high value, high risk customers through predicting churn risk accounts with 81% accuracy.
BrightTarget helped a leading buildings merchants identify £2.9M additional revenue potential from retention & re-activation activity from a 25% reduction of high-value churners and a 0.25% increase in re-activation of high-value lapsers.
Grow – Accurately predict customer needs, identify hidden upsell and cross-sell opportunities and present timely offers, to enhance the overall customer experience.
BrightTarget helped a global industrial manufacturer identify an additional £69m cross-sell opportunity with a predicted conversion rate of 5% over the following 12 months alone.
BrightTarget helped a leading building supplies company achieve 4.75 times increase in conversion rate to sale on a cross sell campaign.
Acquire – Prioritise leads with highest lifetime value potential, generate better leads for sales teams and find prospects that best-match your existing best customers.
BrightTarget helped a leading hi-tech manufacturer achieve a 66% increase in prospect to sales ready lead conversion.
BrightTarget helped a global events company achieve a 180% delegate conversion uplift compared to a controlled data set thanks to better prospect profiling.
Using BrightTarget, these insights are valuable to every customer-touching department from marketing to sales to finance, because customer data is united into a single, quantitative measure: Customer Lifetime Value.
This focus on CLV is a core differentiator for BrightTarget, according to the Forrester Wave: Predictive Marketing Analytics for B2B Marketers report.
For marketing, this means identifying leads with the highest future value so the marketing can focus activity on the right customers in the right way.
For sales, this means identifying the accounts that are likely to be worth most over time, so sales can focus their activities to generate most ROI.
For finance, this means giving concrete financial context to marketing activity, allowing more accurate budgets and forecasts.
For the business, this means customers are at the heart of decision-making, the business meaningfully aligned to the shared customer growth goal.
The point is this: predictive isn’t about making one department or activity more effective. Rather, it’s about shifting how strategic decisions are made; realigning the business to be customer-first, in order to drive growth.
The customer today plays a central role in the growth equation. AI and advanced predictive allows smart organisations transform their vast amounts of customer data into meaningful, intelligent insight that drives business-wide customer alignment.
That’s why the Forrester Wave Report: Predictive Marketing Analytics for B2B Marketers highlights the “growing interest in PMA” thanks to the “real, measurable results” adopters enjoy. In the report BrightTarget is especially recommended for B2B businesses “wanting to drive sustainable business growth through marketing and sales efficiency [and] drive revenue across the entire customer life cycle”.
Download the report here, and find out why predictive marketing analytics should be on the agenda for your organisation.