Customer retention management features
Unification of disparate customer data
Customer 360° views & graph visual analytics
Dynamic segmentation & persona computation
Customer journey mapping
Graph recommenders for next best action, incl. upsell, cross sell
Churn prevention
NLP of unstructured customer data
Customer pattern & behaviour modelling
E-commerce browsing analytics
Customer analytics the graph intelligence way
Customers are opting for convenience and value for money over brand loyalty. So excellent service and a personalised experience is key to maintaining that competitive edge. Consumer data provides valuable insights into shopping behaviour, trends, buying patterns and sentiment.
Locstat LightWeaver®, our graph intelligence platform, collates data from your entire customer journey, across multiple touchpoints and channels, to create a customer 360° view. This improves consumer experience and feeds back into your marketing strategy with enhanced personalisation and segmentation capabilities.
Current CDPs are very good at what they do, but lack the feature engineering and computational power to generate the necessary insights needed for true, value adding customer intelligence.
Our future-ready customer retention management capabilities include Customer 360°, segmentation engines, churn prediction, recommender systems and natural language processing (NLP). Locstat LightWeaver® uses next gen advanced analytics technologies to overcome the functional and technical limitations of traditional solutions:
- Combine multiple important data sets e.g. POS, CRM, customer engagement and loyalty data, to provide an enhanced, context rich and unified data set that supports numerous customer analytics use cases.
- Advanced analytics and computation augment and complement existing customer data platforms e.g. Salesforce.
- Leverage graph-based AI and machine learning to enhance data relationships between people, products and brand.
- Benefit from graph-based multi-data source and touch point customer pattern behaviour.
- High performance customer computation and ML framework supports existing customer data platforms e.g. Salesforce
For retailers and wholesalers; apparel and brands; FMCGs; e-commerce; customer loyalty systems; marketing; communications
Retain your most important asset – your customer!
Enrich the connection with your customer through an enhanced, personalised experience and increase their value with effective marketing strategies to target them when they are most receptive. Our platform supports a holistic retention strategy through its unique combination of capabilities working in seamless harmony:
- Develop a 360° view of each customer and different cohorts of customers.
- Identify opportunities for up and cross sell recommendations to individualise service and maintain brand loyalty.
- Apply customer journey mapping to identify context and insight rich segments that inform new data-driven customer journeys.
- Highlight emerging trends and opportunities for developing innovative products or services.
- Detect customer activity fall-off to minimise avoidable attrition and prevent churn.
- Distribute pertinent information to relevant departments to reduce customer effort when resolving problems.
- Track the effectiveness of marketing efforts with advanced measurement of impact analytics from multiple feedback sources.
- Utilise loyalty scheme information to optimise user engagement, maximise customer value and pre-empt churn.
Customer 360° and customer journey mapping
Customers engage with businesses through multiple touch points and channels such as e-commerce websites, in-store, mobile apps, loyalty and value cards, sales staff and call centres. Viewing these as journeys can accurately predict consumer behaviour. A single 360° customer view in real-time allows timeous and informed decision making that increases profit and creates brand ‘stickiness’ through personalised, contextual engagements.
Recommendation and segmentation engines
Recommender systems personalise customer experience and maximise value through cross and upselling opportunities; segmentation takes it a step further by creating specific target markets for your promotions. Our powerful hybrid recommender system uses complex event processing and graph database technology with machine learning algorithms that continually recalibrate with the influx of data. This combination provides contextualised insights to increase the accuracy and coverage of your recommendations, whilst enhancing the level of nuance for a bespoke customer service.
Segmentation comes as standard so you can choose how to divide your data or customers (e.g. by age, location, customer value, etc.) to implement your strategic marketing campaigns. We also assess for churn before we build your recommender system, fine tuning it to your specific requirements, to ensure early detection (e.g. silent complainers) and mitigate avoidable attrition.
- Graph based, multi-mode, hot and cold start recommendation engine – the who (to engage) and the what (could / should you offer them).
- Dynamic customer segmentation, based on multiple and varied binning features.
- Integrated CEP / rules engine and recommendation engine for next best action initiation.
- ML model operationalisation.
You can’t hide from graph!
Visualise customer interactions
- Achieve a holistic customer 360° paradigm through the unification of consumer data into a graph database.
- Use dynamic graph visual analytics to view all customer data points, touch points and data relationships in a single view.
- View properties and attributes on nodes and edges for enhanced context and understanding.
- Expansion capability to view the full network of touch points through multiple ‘hops-out’ expansion.
Transaction monitoring and analytics
Pipeline and curate multiple customer data sources (POS, loyalty, e-commerce, social media) into a unified (customer 360°) data set available for querying and analytics.
Real-time, streaming analytics and batch data processing and storage.
Transaction monitoring and dynamic CEP / rules engine action to initiate next best action on incoming data messages.
Data aggregation and automated reporting and output generation and orchestration.
Natural language processing
Any customer-centric organisation has unstructured and free text data, which can be mined and analysed for valuable intelligence and consumer insights.
Locstat LightWeaver®’s NLP engine provides powerful, graph supported entity extraction of unstructured customer data from multiple data sources. Graphing this processed data makes it available for graph query analytics such as entity resolution.
The NLP processing output can also be pipelined in as new data streams for the CEP / rules engine to initiate next best action.
Leverage graph-based AI and machine learning to augment our dynamic and probabilistic rules engine – embed ML models into the rules engine.
Process and analyse customer review feedback, sentiment analytics, media articles, call centre note capture, etc. to complete and enhance your customer 360° paradigm.